bluuebunny/crossref_metadata_2025_split huggingface dataset:
Self-Disclosure Experiences of Adults Who Stutter: An Interpretative Phenomenological Analysis
Authors: Young Megan M. , Byrd Courtney T. , Gabel Rodney , White Andrew Z. 
Published: August 2022

Purpose:
Self-disclosure describes the act of revealing personal information to another person. To date, researchers in the area of stuttering have primarily demonstrated the utility of self-disclosure through analysis of listener perceptions. This study explores the utility of informative self-disclosure use from the perspectives of adults who stutter with experience using this strategy over time and across contexts.

Method:
Twelve adults who stutter discussed their self-disclosure experiences in semistructured interviews. Interview transcripts were analyzed using interpretative phenomenological analysis to produce themes reflecting the most salient aspects of self-disclosure experiences. Credibility was achieved through bracketing, investigator triangulation, and member checking.

Results:
Four superordinate themes reflecting experiences shared by all 12 participants were generated. Each superordinate theme contained two to three corresponding subthemes. The superordinate themes included cognitive relief, self-empowerment, social connection, and personalization. These findings reflect the positive impact of informative self-disclosure use on communication and quality of life.

Conclusions:
Adults who stutter perceive informative self-disclosure to be an effective strategy that provides various benefits to the speaker, in addition to facilitating positive listener perceptions. Clinicians should encourage clients to self-disclose in an informative and personalized manner, provide opportunities for practice, and support clients in determining when and where it is most beneficial for them to implement this strategy.
Syntactic Complexity Across Language Sampling Contexts in School-Age Children, Ages 8–11 Years
Authors: Lenhart Michelle H. , Timler Geralyn R. , Pavelko Stacey L. , Bronaugh Dannette A. , Dudding Carol C. 
Published: August 2022

Purpose:
Syntax has been called the structural foundation of language, as its development allows for more efficient and effective communication. Complex syntax production is known to lag in children and adolescents with language impairment. Conversation, narrative, and expository language sampling contexts are recommended tools for the comprehensive assessment of school-age children, including syntactic abilities. Despite these recommendations, few studies have examined syntactic differences obtained from these three sampling contexts in a within group sample of school-age children, (i.e., ages 8–11 years). Information about similarities and differences in syntactic measures obtained from these three sampling contexts is needed to identify the optimal sampling context(s) for eliciting complex syntax.

Method:
Conversational, narrative, and expository language samples were elicited from 85 children with typically developing language ages 8;0–11;11 (years;months). Samples were transcribed and analyzed for the mean length of utterance in words and clausal density, or the number of clauses per communication unit as measured by the subordination index.

Results:
Syntactic measures differed significantly across the three sampling contexts. Namely, narrative and expository language samples elicited longer utterances and more syntactically complex language than conversation samples. Age-related differences in the syntactic measures were not detected.

Conclusions:
Differences in syntactic measures between conversation and narrative samples and conversation and expository samples within children ages 8–11 years support use of narrative and expository contexts as the most appropriate language sampling contexts for elicitation of complex syntax in school-age children ages 8–11 years. Conversation sampling is unlikely to elicit children's capacities for complex sentence production.
Transmission network congestion control by DESS through interval computation and capacity optimization via hybrid DE‐PSO technique
Authors: Asija Divya , Viral Rajkumar , Choudekar Pallavi , Bakhsh Farhad Ilahi , Ahmad Akbar 
Published: August 2022

AbstractTransmission congestion is one of major drawbacks of deregulated power system. Congestion gradually violates the physical, operational and policy constraints of the present electricity market. Congestion management in huge power system remains a challenging and tough task, which can be achieved by introducing one or more Distributed Energy Resources (DERs) such as Distributed Generation (DG), electric vehicles, modern micro grid, Energy Storage Systems (ESSs) etc. over congested lines. Consequently, this work proposes the hourly congestion management by optimal allocation of DG in ‘24 hours’ time frame. Further, Transmission Congestion Rent is used to determine the optimal and sub optimal locations for DG, whereas Differential Evolution and Particle Swarm Optimization based hybrid optimization technique is exploited to identify optimal DG size. In this work, solar based DG along with battery based ESS is considered to act as Distributed Energy Storage System ‘DESS. Subsequently, Interval computation method is introduced in this work to consider the intermittency of solar DG. Battery Energy Storage System ‘BESS’ is integrated with DGs due to its excess energy storage capability during off‐load period and make it available at peak load conditions, thereby enhancing the overall efficiency of the network. The ‘24 hours’ solar irradiance and temperature data of Delhi, India is taken into account to mathematically model the power generated from Solar DG. The proposed methodology is tested on IEEE 30‐bus system and ‘24 hours’ demand data is generated from the original IEEE load data. From the obtained results, it has been established that the hybrid optimization technique results into a better solution as compared to their individual enforcement in managing available generation resources and congestion problem.
A tri‐level approach for coordinated transmission and distribution system expansion planning considering deployment of energy hubs
Authors: Allahvirdizadeh Yousef , Shayanfar Heidarali , Moghaddam Mohsen Parsa 
Published: August 2022

AbstractThis paper presents a tri‐level stochastic coordinated transmission and distribution system expansion (CTDS) planning considering the deployment of energy hubs (EHs) across the distribution systems (DSs). The first level of the proposed optimization approach deals with transmission system expansion planning (TEP), while the second level develops distribution system expansion planning (DEP). Market clearing is done in the third level to update the locational marginal prices (LMPs) for different distribution system operators (DSOs). The EHs include photovoltaic cells (PVs), wind turbines (WTs), combined heating and power units (CHPs), boilers, and electrical and absorption chillers. The proposed tri‐level approach is solved with an iterative algorithm based on the diagonalization approach and tested on the modified IEEE 30‐bus transmission systems (TS) with several DSOs. Each DSO includes 18‐bus electrical, heating, and cooling energy systems. The numerical analysis shows that the total cost of the transmission system operator (TSO) is not changed with implementing the uncoordinated approach. However, the total cost of the whole system is reduced by 6.54% with accommodation of the EHs in the uncoordinated approach. Moreover, the total cost of the TSO as well as the whole system are reduced by 41.11% and 16.96%, respectively, with the proposed (CTDS) planning.
Using optical flow algorithm based on dynamic illumination mode to examine defects on highly reflective turbine blade surface
Authors: Shang Xuan , Song Wenyan , Chen Zhen , Zhang Congxuan 
Published: August 2022

AbstractNotion of optical flow literally refers to the displacements of intensity patterns. In that sense, extracting interested information from 2D scene is analogy to modulation/demodulation in random signal processing. To address the limitations presented in computer vision based on static image, we propose a novel metal component defect detection method, specified as the instance of turbine blade surface detection, using optical flow estimation.To start the specified pattern recognition in 2D presentation, we modulate the brightness constancy assumption equation as illumination varying model, by sampling the second image with function whose frequency was chosen according to the Nyquist sampling theorem, and a sinusoidal factor was introduced as an additive factor. This tunable channel based on 2D image transfers intensity features into optical modes. Then, we implement optical flow estimation on two sequential images. Experimental results reveal grayscale space shows completness in representing the optical modes of turbine blade with various kinds of surface characteristics. By modifying the index of information content, we propose quantitative index to evaluate the performance of our method. Evaluation reveals optical flow algorithm is qualified to examine defects on highly reflective turbine blade, and our method extends the application of optical flow.
A multi‐attention dynamic graph convolution network with cost‐sensitive learning approach to road‐level and minute‐level traffic accident prediction
Authors: Wu Mingyao , Jia Hongwei , Luo Dan , Luo Haiyong , Zhao Fang , Li Ge 
Published: August 2022

AbstractTraffic accident prediction on road levels and minute levels plays an important role in optimizing public safety and improving traffic infrastructure. However, there are still some challenges in this work. Firstly, the dynamic factors (e.g. traffic flow) affecting traffic accidents make the road network have dynamic spatio‐temporal dependency, which leads to biased prediction results. Secondly, the occurrence of traffic accidents is a small probability event, which brings about zero‐inflation problem. To address aforementioned problems, the authors propose a Multi‐Attention Dynamic Graph Convolution Network with Cost Sensitive Learning approach (MADGCN). Specifically, in the spatial dimension, MADGCN calculates the attention scores of different types of dynamic factors through attention mechanism to simulate the different influence degrees of different factors, and models dynamic inter‐road spatial correlation through Graph Convolution Network (GCN). In the temporal aspect, MADGCN adaptively models the dynamic temporal correlations through self‐attention blocks. In addition, MADGCN improves the loss function based on cost‐sensitive learning strategy to increase the cost of false classification of positive samples, so as to accurately mine sparse positive samples. Experimental results on two real‐world traffic accident datasets demonstrate the superiority of MADGCN. Compared with the existing state‐of‐the‐art methods, F1‐score of MADGCN on two real‐world traffic accident datasets is improved by 11.61% and 9.15%, respectively.
Modelling and output voltage distortion with capacitive current feedback control for single phase inverter powering non‐linear load
Authors: Zhong Minghang , Tong Xiangqian 
Published: August 2022

AbstractThe pulse width modulation inverter is widely applied in independent PV renewable generation applications and uninterruptible power supplies. Many control schemes are investigated for the inverter feeding non‐linear loads, aiming to achieve the desired performance. However, the model currently proposed is mostly based on a linear load, which is not suitable for the condition with the non‐linear load. In this paper, the uncontrolled diode rectifier load model based on the AC and DC link power balances is analysed in detail first. Then, the rectifier inverter control system mathematical model is presented. The mathematical model derivation considers the rectifier load, especially non‐linear dead zone circuit performance that is closer to practical application conditions. Based on the proposed model, the output voltage control strategy with capacitor current feedback is further given. The operating principle of the proposed model and control scheme is analysed in detail. Additionally, the conclusions are validated by simulations and experimental results.
CHAC1 as a novel biomarker for distinguishing alopecia from other dermatological diseases and determining its severity
Authors: Karami Hassan , Nomiri Samira , Ghasemigol Mohammad , Mehrvarzian Niloufar , Derakhshani Afshin , Fereidouni Mohammad , Mirimoghaddam Masoud , Safarpour Hossein 
Published: August 2022

AbstractAlopecia Areata (AA) is characterised by an autoimmune response to hair follicles (HFs) and its exact pathobiology remains unclear. The current study aims to look into the molecular changes in the skin of AA patients as well as the potential underlying molecular mechanisms of AA in order to identify potential candidates for early detection and treatment of AA. We applied Weighted Gene Co‐expression Network Analysis (WGCNA) to identify key modules, hub genes, and mRNA–miRNA regulatory networks associated with AA. Furthermore, Chi2 as a machine‐learning algorithm was used to compute the gene importance in AA. Finally, drug‐target construction revealed the potential of repositioning drugs for the treatment of AA. Our analysis using four AA data sets established a network strongly correlated to AA pathogenicity based on GZMA, OXCT2, HOXC13, KRT40, COMP, CHAC1, and KRT83 hub genes. Interestingly, machine learning introduced these genes as important in AA pathogenicity. Besides that, using another ten data sets, we showed that CHAC1 could clearly distinguish AA from similar clinical phenotypes, such as scarring alopecia due to psoriasis. Also, two FDA‐approved drug candidates and 30 experimentally validated miRNAs were identified that affected the co‐expression network. Using transcriptome analysis, suggested CHAC1 as a potential diagnostic predictor to diagnose AA.
First absolute wind measurements in Saturn’s stratosphere from ALMA observations
Authors: Benmahi B. , Cavalié T. , Fouchet T. , Moreno R. , Lellouch E. , Bardet D. , Guerlet S. , Hue V. , Spiga A. 
Published: August 2022

Context. Past observations of Saturn with ground-based and space telescopes have enabled the monitoring of tropospheric wind speeds using cloud-tracking techniques. The most remarkable feature is a broad and fast prograde jet at the equator that reaches speeds of ~400 m s−1. Saturn’s stratospheric dynamics are less well-known. At low latitudes, they are characterized by the thermal signature of an equatorial oscillation; the observed thermal structure implies that there is a strong oscillating vertical shear of the zonal winds throughout the stratosphere. However, wind speeds in this region cannot be measured by cloud-tracking techniques and remain unknown.
Aims. The objective of this study is to measure directly and for the first time the zonal winds in Saturn’s stratosphere using the ALMA interferometer.
Methods. We observed the spectral lines of CO at 345.796 GHz and HCN at 354.505 GHz with the high spatial (~0.6″ × 0.5″) and spectral resolutions enabled by ALMA, and measured the Doppler shift induced by the winds on the lines at the planet limb where the emission is the strongest. After subtracting the beam-convolved planet rotation, we derived the zonal wind speeds as a function of latitude.
Results. We measured the zonal winds from ~20°S to the northern polar latitudes. Latitudes between 20°S and 45°S were obscured by the rings and were inaccessible southward of 45°S. The zonal wind profiles obtained on the eastern and western limbs are consistent within the error bars and probe from the 0.01 to the 20 mbar level. We most noticeably detect a broad super-rotating prograde jet that spreads from 20°S to 25°N with an average speed of 290 ± 30 m s−1. This jet is asymmetrical with respect to the equator, a possible seasonal effect. We tentatively detect the signature of the Saturn semi-annual oscillation (SSAO) at the equator, in the form of a ~−50 ± 30 m s−1 peak at the equator which lies on top of the super-rotating jet. We also detect a broad retrograde wind (−45 ± 20 m s−1) of about 50 m s−1 in the mid-northern latitudes. Finally, in the northern polar latitudes, we observe a possible auroral effect in the form of a ~200 m s−1 jet localized on the average position of the northern main auroral oval and in couter-rotation, like the Jovian auroral jets.
Conclusions. Repeated observations are now required to monitor the temporal evolution of the winds and quantify the variability of the SSAO jet, to test the seasonality of the asymmetry observed in the broad super-rotating jet, and to verify the presence of auroral jets in the southern polar region of Saturn.
Arthroscopic rotator interval release for frozen shoulder, comparative study between diabetic and non-diabetic patients
Authors: Tawfeek Wessam , Addosooki Ahmad , Elsayed Moustafa 
Published: August 2022

Introduction: The objective of this study is to evaluate the outcomes of arthroscopic rotator interval release for the treatment of frozen shoulder and compare the results in patients with and without diabetes. Methods: thirty-two patients with frozen shoulders were divided into two groups; 19 diabetics and 13 non-diabetics. All patients underwent arthroscopic rotator interval release. The VAS and UCLA score were assessed pre-operatively and post-operatively; after 1, 3, and 12 months and compared between groups. Results: The VAS and UCLA score was significantly improved in both groups during follow-up intervals (p < 0.01). There was no significant difference between diabetic and non-diabetic patients in VAS and UCLA scores during follow-up times (p-values > 0.05). Conclusion: Arthroscopic rotator interval release provides significant improvement of frozen shoulder with no difference in results between diabetic and non-diabetic patients.
Level of evidence: Level 2; Prospective Comparative study.
Brønsted Acid Catalyzed Carbocyclizations Involving Electrophilic Activation of Alkynes
Authors: Toullec Patrick Y. , Hermange Philippe , Gicquiaud Julien , Barbier Morgan , Karnat Alexandre 
Published: August 2022

AbstractThis review focuses on the carbocyclization reactions of alkyne-containing substrates catalyzed by Brønsted acids. The electrophilic activation occurs either by direct protonation of the alkyne or by formation of an intermediate cation that further reacts with the alkyne to give a key vinyl cation intermediate. Specific focus is placed on the selectivity of the various methodologies described herein and on mechanistic rationales.1	Introduction2	Brønsted Acid Catalyzed Alkyne Carbocyclization Involving C(sp) Reaction Partners2.1	Brønsted Acid Catalyzed Cyclization of Diynes2.2	Brønsted Acid Catalyzed Cyclization of Allenynes3	Brønsted Acid Catalyzed Alkyne Carbocyclization Involving C(sp2) Reaction Partners3.1	Brønsted Acid Catalyzed Cycloisomerization of Enynes3.1.1	Initial Protonation of the Alkene Function3.1.2	Initial Protonation of the Alkyne Function3.1.3	A Conia-Ene Reaction3.2	Electrophile-Induced Carbocyclization Involving Other C(sp2)-Based Reaction Partners3.2.1	Iminium Electrophiles3.2.2	Oxonium Electrophiles3.2.3	Isocyanate and Thioisocyanate Electrophiles3.3	Brønsted Acid Catalyzed Cycloisomerization of Aryl-alkynes3.3.1	Reactions Using Excess or Stoichiometric Amounts of Brønsted Acid3.3.2	Reactions Using Substoichiometric Amounts of Brønsted Acid3.3.3	Heteroatom-Substituted Alkynes3.3.4	Enantioselective Brønsted Acid Catalyzed Cycloisomerization of Aryl-alkynes4	Brønsted Acid Catalyzed Alkyne Carbocyclization Involving C(sp3) Reaction Partners: Alkyne-alkane Cycloisomerization5	Conclusion and Outlook
Construction and Characterization of a Diphase Two-Dimensional Halogen-Bonded Organic Framework Based on a Pyrene Derivative
Authors: Chen Shigui , Gong Guanfei , Xie Fei , Wang Lu , Wang Jike 
Published: August 2022

AbstractCrystalline porous materials have received extensive attention due to their fascinating structures and wide range of applications. We report a novel diphase two-dimensional (2D) halogen-bonded organic framework (XOF-TPP) based on 1,3,6,8-tetra(pyridin-4-yl)pyrene (TPP). XOF-TPP was constructed through [N···I+···N] interactions between the pyridyl groups of TPP and iodonium cations. The formation of XOF-TPP was monitored by X-ray photoelectron spectroscopy, IR spectroscopy, powder X-ray diffraction, scanning electron microscopy, and high-resolution transmission electron microscopy, and simulated theoretically. Small-angle X-ray scattering indicated that the XOF-TPP exists as a 2D periodic structure. This diphase 2D halogen-bonded organic framework has promise for practical applications in supramolecular functional materials.
Unwrapping a full temporal cycle in time domain thermoreflectance for enhanced measurement sensitivity in thermally insulating materials
Authors: Donovan Brian F. , Gray Taylor L. , Wilson Adam A. , Warzoha Ronald J. 
Published: August 2022

Time delayed pump–probe measurement techniques, such as Time Domain Thermoreflectance (TDTR), have opened up a wealth of opportunities for metrology at ultra-fast timescales and nanometer length scales. For nanoscale thermal transport measurements, typical thermal lifetimes used to measure thermal conductivity and thermal boundary conductance span from sub-picosecond to ∼6 nanoseconds. In this work, we demonstrate a simple rearrangement and validation of a configuration that allows access to the entire 12.5 ns time delay available in the standard pulse train. By reconfiguring a traditional TDTR system so that the pump and probe arrive concurrently when the delay stage reaches its midpoint, followed by unwrapping the temporal scan, we obtain a dataset that is bounded only by the oscillator repetition rate. Sensitivity analysis along with conducted measurements shows that great increases in measurement sensitivity are available with this approach, particularly for thin films with low thermal conductivities.
Reconstructing non-contrastive stress in Austronesian and the role of the mora in stress shift, gemination and vowel shift
Authors: Smith Alexander D. 
Published: August 2022

AbstractCompeting schools of thought on the reconstruction of Proto-Austronesian stress contend that primary stress was either regular (falling on the penultimate syllable with possible phonetic conditions that triggered stress shift to the final syllable) or lexical (falling unpredictably either on the penult or ultima). In this study, I argue that the comparative evidence supports the first position: that primary stress fell regularly on the penultimate syllable and was not lexical. Further, primary stress was repelled to the final syllable if the penultimate syllable was open and contained a schwa nucleus. Three Austronesian first-order subgroups, Malayo-Polynesian, Western Formosan, and Paiwan, are shown to directly continue the reconstructed stress system of Proto-Austronesian, with stress falling regularly on the penultimate syllable but shifting to the final syllable after a schwa.I also argue that the inability of schwa to hold stress is a result not of quality, but rather of quantity, as it is shown that schwa was a zero-weight vowel in Proto-Austronesian. Words with a schwa in the penultimate syllable, CəCVC, are shown to be sub-minimal, containing only a single mora. Daughter languages in Malayo-Polynesian underwent multiple cases of phonologically motivated drift, including consonant gemination, the deletion of penultimate schwa in three-syllable words, and vowel shift. These sound changes are argued to be part of a phonological conspiracy whose outcome is the addition of a mora to sub-minimal words. This study therefore offers both a reconstruction of Proto-Austronesian stress as well as a phonological explanation for these various sound changes in Malayo-Polynesian.