bluuebunny/crossref_metadata_2025 huggingface dataset:
A systematic approach to mapping tectonic faults and documenting supporting geomorphology
Authors: Adam Rachel N. , Scott Chelsea , Arrowsmith J Ramón , Reano Darryl , Madugo Chris , Koehler Rich D. , Zuckerman Malinda G. , Gray Brian , Kozaci Ozgur , González Tania , AbramsonWard Hans , Rockwell Thomas K. , Gath Eldon , Kottke Albert R. , Leuchter Ethan
Published: January 2025

Mapping tectonic faults is challenging because mapping approaches are not standardized and some evidence for faulting is ambiguous due to surface processes that obscure the geomorphology. We developed and evaluated a new systematized approach for mapping faults and documenting geomorphic evidence based on desktop mapping using remote sensing data. Our approach works as a teaching tool to introduce fault mapping and in industry settings to establish consistent documentation. Using our approach, a mapper maps the landscape morphology, geomorphology, and surficial geology. The mapper uses the geomorphic indicator ranking approach to document the geomorphic indicators that support faulting such as scarps, triangular facets, and deflected streams. The resulting fault maps facilitate straightforward dissemination of information and build toward more accurate depictions of fault traces, which support understanding fault processes and predicting coseismic rupture location in a future earthquake.

We evaluated our mapping approach as follows. (1) We qualified the geomorphology that best predicts future rupture location as having the lowest geomorphic indicator-to-rupture separation distance. Of the features tested, cut or offset alluvial fans, fault scarps, and lineaments performed the best. (2) We found similarities in the fault confidence rankings chosen by the mappers and those calculated from the mapped geomorphology. (3) To explore best practices in fault mapping, we conducted listening sessions with 18 participants and found that terminology and mapping process vary by experience level. More-experienced mappers tend to use more technical terms to describe the geomorphology while less-experienced mappers use vague descriptions and generalize nearby features.
Impact dynamics of flow-type landslides on V-shaped diversions: combined numerical and experimental approach
Authors: Li Ruoying , Choi Clarence E. , Gong Xinglong
Published: January 2025

In sparsely populated and rural areas, government agencies propose the installation of V-shaped diversions to mitigate flow-type landslides. In contrast to rigid barriers, diversions are small, easy-to-construct, and cost-effective. Nonetheless, the impact dynamics of flow-type landslides against diversion structures remains unclear and hinders the development of scientific-based design guidelines. Diversion angles that are too large decelerates the flow and causes an overspill. In contrast, diversion angles that are too small results in long walls that are not feasible to construct. In this study, laboratory-scale flume experiments modeling the impact of dry sand against diversions are conducted. The experimental data are used to validate a coupled material point method and discrete element method numerical model. The numerical model is used to conduct a parametric study to investigate the effects of post-impact flow. The transition from attached oblique to detached bow shocks occurs with decreasing inflow and increasing diversion angle, causing the largest flow runup height at the diversion side rather than the diversion apex. It is proposed to design diversions based on bow and oblique shock mechanisms. Design charts that consider the competing effects between deflected and accumulated state are proposed. The newly proposed analytical model for predicting deflection height to mitigate overspill shows close agreement with experimental results.
Biocontrol of the pine processionary moth, Thaumetopoea wilkinsoni (Tams.) (Lepidoptera: Notodontidae) by forest-derived entomopathogenic fungi
Authors: Koç Muhammed , Bekircan Eski Duygu , Eski Ardahan
Published: January 2025

The pine processionary moth (PPM), Thaumetopoea wilkinsoni Tams. (Lepidoptera: Notodontidae), is an important forest pest in the Mediterranean region. This study demonstrated for the first time the biocontrol potential of entomopathogenic fungi (EPF) isolated from pine forest soils on Thaumetopoea wilkinsoni. The identity of five isolates obtained by the Tenebrio-bait method was established by macroscopic and microscopic features and ITS-rDNA sequencing. Pathogenicity and virulence of novel indigenous isolates on fourth stage larvae of Thaumetopoea wilkinsoni were then determined. PPM1, PPM3, and PPM5 were identified as Beauveria bassiana Vuill. (Hypocreales: Cordycipitaceae); PPM2 and PPM4 were identified as Fusarium oxysporum Schlecht. (Hypocreales: Nectriaceae). All isolates were found to be pathogenic at a concentration of 107 conidia/mL, with virulence varying between 15% and 100%. The pathogenicity of Fusarium oxysporum on Thaumetopoea wilkinsoni was demonstrated for the first time in this study and its virulence was determined to be 76%. In addition, the virulence of Beauveria bassiana PPM1 isolate reached 100% at a concentration of 107 conidia/mL 14 days after treatment. Moreover, the median lethal concentration (LC50) required to kill 50% of the larval population was estimated to be 5.7 × 103 conidia/mL. Our results are important to improve the application of new EPF species as biological control agents in pest management.
A Method for Identifying the Vibration Displacement of Deep-Water Pile Foundation Bridge Piers on Soft Soil Foundation Based on Multi-Source Information Fusion
Authors: Wei Qiao , Xiaojian Xu , Yu Cheng
Published: January 2025

There are significant identification errors in the vibration displacement identification of deep-water pile foundation bridge piers on soft soil foundations. Therefore, this paper proposes a new method for identifying the vibration displacement of deep-water pile foundation bridge piers on soft soil foundations based on multi-source information fusion. The characteristics of soft soil structure are analyzed and the stress relationship between soft soil and solid soil skeleton is calculated. Deep water pile foundation bridge piers on soft soil foundation determine the structural characteristics of deep water pile foundation bridge piers on soft soil foundation, construct displacement curves based on the elastic deformation curvature of deep water pile foundation bridge piers on soft soil foundation, and determine the curvature of each point when the bridge pier displacement occurs. Analyze the factors that cause the vibration of deep-water pile foundation bridge piers on soft soil foundations, and determine the characteristics of the vibration of deep-water pile foundation bridge piers on soft soil foundations by calculating the amplitude under different factors. Analyze the different failure modes and shear strength, bending strength, displacement ductility coefficient under the vibration conditions of bridge piers, and analyze the load on the bridge piers to complete the extraction of multi-source information on the vibration displacement of deep-water pile foundation bridge piers on soft soil foundation. Analyze the multi-source information fusion structure, introduce the least squares support vector machine method to complete the fusion of information on the vibration displacement impact of deep-water pile foundation bridge piers on soft soil foundation. Based on this, select strain measurement points for deep-water pile foundation bridge piers on soft soil foundation, and arrange displacement identification along the entire bridge pier at equal intervals to achieve accurate displacement identification. The experimental results show that the proposed method reduces the error of displacement recognition.
Research on the Management of Hybrid AC/DC Microgrids for Electric Vehicles Based on Innovative Algorithms
Authors: Liu Baosheng
Published: January 2025

The AC/DC microgrid-based charging station utilizes renewable resources, operating off-grid and on-grid based on charging demand, and trading electricity with the main grid when required. The diverse nature of hybrid AC/DC systems makes voltage stability a challenge in the present AC/DC microgrid management environment. Traditional algorithms have challenges in ensuring the appropriate cost of power purchased from Distributed Generators (DGs), start-up and shutdown, power switching, AC/DC demand balance, feeder thermal limit, bus voltage limit, the radiality of the microgrid system and connected Electric Vehicles (EVs) become more prevalent. In this study, a novel Optimized Feedforward Neural Network with Elephant Herding Intelligence (OFNN-EHI) has been proposed to handle AC/DC hybrid microgrids energy regulation issues and preserve power stability in hybrid AC/DC systems. The OFNN was used to identify the feeder line status and EHI is used to boost up the classification parameters. The simulation setup integrates an OFNN-EHI approach with an IEEE 33-bus AC/DC microgrid, allowing power exchange at bus 11. The ML model optimizes energy management, enhances stability and preserves power quality by dynamically controlling micro-turbines and wind turbines. According to research, the OFNN-EHI technique considerably improves energy management in hybrid AC/DC microgrids by maintaining constant voltage levels and power quality, outperforming standard algorithms in dealing with operational problems, and improving stability, power quality and cost efficiency.
Coal Transportation Cost Optimization Based on Improved Population Intelligence Algorithm
Authors: Wang Hongfeng
Published: January 2025

In order to improve the profitability of coal enterprises, ensure the reasonable allocation of coal resources, and meet the dynamic changes of the coal transportation market and environment, a coal transportation cost optimization method based on improved group intelligence algorithm is proposed. Based on the characteristics of coal transportation, analyze its transportation mode, fully combining the cost characteristics of different transportation modes, construct the cost minimization optimization objective function including road transportation, railroad transportation and sea transportation, and determine the corresponding constraints; through the particle swarm optimization (PSO) algorithm to solve the objective function that meets the constraints. In order to better respond to the market changes, the concave function and dynamic adjustment mechanism are introduced to optimize and adjust the inertia weights and acceleration constants, so that the algorithm can automatically adjust the optimization strategy according to the changes of the market and the environment to ensure that the transportation scheme is always kept in the optimal or near-optimal state, and finally obtain the optimal cost strategy for coal transportation. Through the experimental verification, the method can achieve better coal transportation cost optimization, effectively reduce the carbon emission and waste of equipment resources in the transportation process, improve the efficiency of coal transportation, and effectively save the cost of coal transportation.
Construction of gyrogroups via group actions by automorphism
Authors: Suksumran Teerapong
Published: January 2025

This paper deals with an admissible AR-group, which is a group admitting an action on itself by automorphism (or, alternatively, an automorphism representation on itself) satisfying a certain nice property. Then it is shown that this group gives rise to a nonassociative group-like structure called a gyrogroup via the method of forming semidirect products. Several families of admissible AR-groups are also determined.
q-analogue of a p-harmonic mapping
Authors: Porwal Saurabh , Mishra Omendra , Murugusundaramoorthy G.
Published: January 2025

The primary objective of this paper is to explore a novel subclass [Formula: see text] of [Formula: see text]-harmonic mappings, along with the associated subclass [Formula: see text]. We demonstrate that the mapping [Formula: see text] is both univalent and sense-preserving within the unit disk [Formula: see text]. Furthermore, we determine the extreme points of [Formula: see text] and establish that [Formula: see text] is defined. Additional results include the derivation of distortion bounds, the convolution condition, and the convex combination for this subclass. Finally, we examine the class-preserving integral operator and introduce a [Formula: see text]-Jackson type integral operator.
Decoding Fake News and Hate Speech: A Survey of Explainable AI Techniques
Authors: Ngueajio Mikel K. , Aryal Saurav , Atemkeng Marcellin , Washington Gloria , Rawat Danda
Published: January 2025

This survey emphasizes the significance of Explainable AI (XAI) techniques in detecting hateful speech and misinformation/Fake news. It explores recent trends in detecting these phenomena, highlighting current research that reveals a synergistic relationship between them. Additionally, it presents recent trends in the use of XAI methods to mitigate the occurrences of hateful land Fake contents in conversations. The survey reviews state-of-the-art XAI approaches, algorithms, modeling datasets, as well as the evaluation metrics leveraged for assessing model interpretability, and thus provides a comprehensive summary table of the literature surveyed and relevant datasets. It concludes with an overview of key observations, offering insights into the prominent model explainability methods used in hate speech and misinformation detection. The research strengths, limitations are also presented, as well as perspectives and suggestions for future directions in this research domain.
A Multimodal Approach for Hate and Offensive Content Detection in Tamil: From Corpus Creation to Model Development
Authors: Mohan Jayanth , Mekapati Spandana Reddy , B Premjith , G Jyothish Lal , Chakravarthi Bharathi Raja
Published: January 2025

Detecting hate speech on social media platforms is vital to mitigate technology-facilitated violence (TFV). Extensive research has targeted widely spoken languages like English, but there’s a notable gap in studying hate speech detection in low-resource languages like Tamil. Additionally, with social media platforms now supporting various modalities, including text, speech, and video, effective techniques for hate speech detection in multimodal formats, especially videos, are crucial. However, detecting hate speech in Tamil presents unique challenges due to its morphology and code-mixing nature. This paper presents a comprehensive approach for detecting hate speech in Tamil, with a focus on multimodal data. We introduce a new dataset, the Multimodal Tamil Hate (MATH) dataset, comprising videos along with their audio and textual transcripts, annotated with four categories of hate speech: offensive, sexist, racist, and casteist. To classify hate speech categories, we leverage transformer-based models. Through a series of experiments, we evaluated the performance of each modality individually and explored their fusion using multimodal approach. BERT-based models were used for textual analysis to extract informative features, the TimeSformer model was employed for video modality, and Wav2vec2 was used for audio modality. Specifically, we attained 81.82% accuracy and a 68.65% F1 score for the text modality, 63.63% accuracy and a 50.60% F1 score for the audio modality, and 45.45% accuracy and a 33.64% F1 score for the video modality. By integrating optimal combinations of models from each modality and employing machine learning classifiers, we achieved an accuracy of 81.82% and an F1 score of 66.67% in our hate speech classification task. Our research findings highlight the effectiveness of employing a multimodal approach for hate speech detection in Tamil, showcasing its efficacy in curbing the dissemination of hateful content on social media platforms.
Mixed Attention and Channel Shift Transformer for Efficient Action Recognition
Authors: Lu Xiusheng , Hao Yanbin , Cheng Lechao , Zhao Sicheng , Liu Yutao , Song Mingli
Published: January 2025

The practical use of the Transformer-based methods for processing videos is constrained by the high computing complexity. Although previous approaches adopt the spatiotemporal decomposition of 3D attention to mitigate the issue, they suffer from the drawback of neglecting the majority of visual tokens. This paper presents a novel mixed attention operation that subtly fuses the random, spatial, and temporal attention mechanisms. The proposed random attention stochastically samples video tokens in a simple yet effective way, complementing other attention methods. Furthermore, since the attention operation concentrates on learning long-distance relationships, we employ the channel shift operation to encode short-term temporal characteristics. Our model can provide more comprehensive motion representations thanks to the amalgamation of these techniques. Experimental results show that the proposed method produces competitive action recognition results with low computational overhead on both large-scale and small-scale public video datasets.
Multigranularity Feature Aggregation and Cross-level Boundary Modeling for Temporal Action Detection
Authors: Li Qiang , Liu Di , Zu Guang , Li Sen , Sun Hui , Wang Jianzhong
Published: January 2025

This paper presents a temporal action detection (TAD) method with multi-granularity feature aggregation and cross-level boundary modeling (MGCBM). Compared with other methods, our proposed approach has the following advantages. First, different from most existing works which only consider the local temporal context, a simple and computationally efficient Multi-Granularity (MG) module is proposed to comprehensively extract video features in instant, local and global temporal granularities. Second, unlike the methods that only employ the information from single feature pyramid level for action boundary regression, a cross-level boundary modeling (CBM) strategy that integrates the relative information from both the same and higher level features is designed to improve the accuracy of boundary prediction. At last, benefiting from the MG module and CBM strategy, our method outperforms other state-of-the-art approaches on five challenging TAD datasets: THUMOS14, MultiTHUMOS, EPIC-KITCHENS-100, ActivityNet-1.3 and HACS. We make our code and pre-trained model publicly available at:
https://github.com/MGCBM/TAL-MGCBM
.
Dual-View Learning from Crowds
Authors: Zhang Huan , Jiang Liangxiao , Zhang Wenjun , Webb Geoffrey I.
Published: January 2025

Crowdsourcing services provide a fast and cheap way to obtain substantial labeled data by employing crowd workers on the Internet. In crowdsourcing learning, two-stage methods have been widely used, which first infer the integrated label for each instance and then build a learning model using instances with their integrated labels. However, existing two-stage methods mainly focus on how to infer more accurate integrated labels, after that, most of them directly regard the integrated labels as class labels to build a learning model, which loses the detailed worker labeling information in multiple noisy labels and thus results in sub-optimal model accuracy. To solve this problem, in this study, we take the multiple noisy labels of each instance as its attribute value vector to construct another view in addition to the original attribute view, and propose a novel two-stage method called dual-view learning from crowds (DVLFC). In DVLFC, we first pick out workers with sufficient number of labels and augment the multiple noisy label set for each instance, then we build a supervised learning model in each view and at last we fuse their class-membership probabilities to get the final classification result. Extensive experiments on both real-world and artificial crowdsourced datasets prove the effectiveness of DVLFC.
Pattern-oriented Attention Mechanism for Multivariate Time Series Forecasting
Authors: Hu Hanwen , Han Zhangchi , Qian Shiyou , Yang Dingyu , Cao Jian , Xue Guangtao
Published: January 2025

Multivariate time series forecasting is applied in many domains, such as finance, transportation, and industry. The main challenge of precise forecasting lies in accurately capturing latent dependencies. Recent studies develop various frameworks to reduce computational complexity or to enhance the learning of intricate relationships, while lacking interpretability and generality. In this article, we aim to elucidate the capture of dependencies as the recognition of patterns. We believe that patterns can be formally described from two aspects: the shapes of segments that frequently repeat and the corresponding forms of repetitions. Drawing upon this idea, we design a multivariate time series forecasting model named
PRformer
,

1

which incorporates a pattern-oriented attention mechanism and a pattern-based projector. The attention mechanism can perceive different forms of repetitions by embedded with various similarity evaluation metrics between segments, and filter out noise from segments to extract potential patterns with a statistical-driven weighting scheme. The pattern-based projector is employed to form the forecasting results by deriving the representative patterns from the set of potential ones. By incorporating explicit definitions of patterns, PRformer is interpretable and general to various time series scenarios. Experimental results on seven datasets demonstrate that PRformer outperforms six state-of-the-art models by about 10.7% in forecasting accuracy.
Frontier model chatbots can help instructors create, improve, and use learning objectives
Authors: Crowther Gregory J. , Funk Merrill D. , Hennessey Kelly M. , Lawrence Marcus M.
Published: January 2025

Amid much recent interest in the impact of generative artificial intelligence on education, one relatively underexplored issue is the extent to which instructors can use chatbots to work more efficiently. This study determined whether the challenging tasks of writing learning objectives (LOs) and writing LO-linked assessment questions can be delegated to advanced chatbots. The chatbots’ outputs were often impressive yet often imperfect and thus can be useful as solid drafts that still require instructor oversight.
Characterization of FAM114A1: a novel podocyte cytoskeleton-associated protein upregulated in glomerular injury
Authors: Hayashi Norifumi , Kumar Sudhir , Trivin-Avillach Claire , Fan Xueping , Stoddard Shana V. , Akai Ryoko , Fujimoto Keiji , Iwawaki Takao , Yokoyama Hitoshi , Furuichi Kengo , Beck Laurence H.
Published: January 2025

Podocyte cytoskeletal proteins are crucial for podocyte integrity and maintenance of slit diaphragms as urinary filtration barriers. In this study, we focused on a novel protein, FAM114A1, that was the top classifier gene in MN in the gene expression study. We show that FAM114A1 is a podocyte-specific protein in the kidney and is upregulated in glomerular injury. FAM114A1 is associated with the podocyte cytoskeleton and silencing FAM114A1 affected podocyte cell morphology and functions.
The Prognostic Factors in Children With Status Epilepticus and Status Epilepticus Severity Score Scales
Authors: Bilge Serap , Mert Gülen Gül , Hergüner Özlem , İncecik Faruk , Altunbaşak Şakir , Yıldızdaş Dinçer , Horoz Özden Özgür , Kuşcu Duygu
Published: January 2025

Background: According to the International League Against Epilepsy (ILAE) 2015 classification, status epilepticus (SE) is a seizure that lasts longer than 5 min or a frequency of more than one seizure within 5 min, without returning to a normal level of consciousness between episodes. In this study, we aimed to evaluate the prognostic factors of SE and compare our patients with those of patients treated internationally with the modified status epilepticus severity score (mSTESS) to determine the reliability of this scoring system.

Methods: The medical records of patients aged 1 month–17 years with SE who were treated at Çukurova University–Balcalı Training and Research Hospital between September 2018 and September 2021 and who were followed in the intensive care unit were included in the study.

Results: Seventy‐two patients were included in this study. The mean age of the patients with SE was 5 years (3–8). The male/female ratio was 34 (47%)/38 (53%). A history of epilepsy was present in 53% of the patients. The most common etiologies behind SE were meningoencephalitis (19%), febrile status (8%), unknown status (12%), and genetic causes (7%). Comorbidities, including developmental delay/intellectual disability, cerebral palsy, hyperactivity, and autism spectrum disorder, were present in 44 (61%) of the patients. The cutoff was ≥ 2 for unfavorable outcomes and 4 for mortality in our patients according to the mSTESS system. The case mortality rate was 1% in our study. Nonconvulsive SE, slowing and abnormal ground on EEG, being stuporous or comatose, having abnormal MRI–CT, and having a comorbid condition were associated with an unfavorable prognosis in SE patients.

Conclusion: The mSTESS is a useful and practical scoring system for predicting the prognosis of SE patients. Nonconvulsive SE, slowing and abnormal ground in EEG, being stuporous or comatose, abnormal MRI–CT, and the presence of comorbid conditions indicated poor prognosis of SE in children.
Revascularization of an Autotransplanted Mature Tooth After Extraoral Root Resection: A Case Report
Authors: Marton Juraj , Mozoľa Michal , Žižka Radovan , Pokorný Zdeněk
Published: January 2025

The outcome of tooth autotransplantation depends mainly on the transplant tooth’s anatomy—the type of donor tooth and the developmental stage of root formation. Mature teeth display a higher complication rate due to lower pulp revascularization potential, requiring root canal treatment (RCT) pre‐ or postoperatively to avoid postoperative complications, which extends treatment duration and cost. This report details a 39‐year‐old patient’s autotransplantation of a mature wisdom tooth to replace the first molar after unsuccessful root canal retreatment. During the surgery, an extraoral root resection of the transplanted tooth was performed prior to placement to avoid the need to elevate the Schneiderian membrane, which displayed imperfect healing following the surgical removal of a cystic lesion in the maxillary sinus. RCT was not performed before nor after the procedure. At the 3‐year follow‐up, the tooth was asymptomatic. The vitality of the autotransplanted tooth was difficult to determine using standard vitality tests, which depend on patients’ subjective responses, but the use of pulse oximetry objectively confirmed this. This case not only shows the possibility of a mature tooth transplant revascularization in an older patient but also gives a possible postoperative protocol of how to objectively confirm and measure the revascularization of the autotransplanted tooth.
Optimizing Young Jackfruit (Artocarpus heterophyllus Lam.) Processing for Plant‐Based Meatballs: Impact of Thermal Treatments on Quality Parameters and Organoleptic Properties
Authors: Samutsri Wisutthana , Thimthuad Sujittra
Published: January 2025

As global demand for plant‐based foods increases due to their nutritional and environmental benefits, young jackfruit (Artocarpus heterophyllus) is emerging as a promising meat alternative. This study evaluates the effects of heat treatments—specifically blanching for 5 min and boiling for 15, 30, and 45 min—on the quality and sensory attributes of jackfruit‐based meatballs. The results indicate consistent color values (L∗, a∗, and b∗) across the samples, with L∗ values ranging from 53.68 to 54.92 and a∗ values from 3.02 to 3.38. The browning index increased with longer boiling times, while the water holding capacity improved from 2.22 to 4.35 as the cooking time extended. Blanching increased the hardness (536.93 g) and springiness (8.30%) of the meatballs. However, these properties decreased with longer boiling times, reaching 317.44 g and 7.68%, respectively, after 45 min. Sensory analysis revealed a strong preference for meatballs made from young jackfruit boiled for 45 min, with the highest score in appearance, flavor, and overall acceptability. These findings suggest that boiling young jackfruit for 45 min optimizes its texture and sensory qualities, highlighting its potential as a sustainable, nutritious, and appealing ingredient for plant‐based meat substitutes.
Reestruturação de encontros obstruinte-líquida
Authors: Cantoni Maria Mendes
Published: January 2025

In Portuguese, CCV syllables form obstruent-liquid clusters and can be optionally restructured by (1) inserting a vowel between the onset consonants, resulting in CV.CV, or (2) deleting the liquid consonant in the second position, resulting in CV, cases that were evaluated separately in previous studies. This study presents an integrated evaluation of the CCV~CV.CV~CV alternation in Brazilian Portuguese, based on acoustic analysis of CCV occurrences in spontaneous speech recordings from 22 native speakers. We sought to determine the role of linguistic factors, such as the position of the accent, as well as evaluate the quality of the epenthetic vowel and duration patterns resulting from consonant loss or vowel insertion. In terms of its quality, the supporting vowel is a centralized vowel, and there may be harmony with the following vowel. It was found that the CV pattern is more frequent in a non-accented context and leads to vowel lengthening, while the CV.CV pattern is more frequent in an accented context. The results are discussed in terms of the gradualness and dynamicity of the phenomenon and considering phonological principles of syllabic restructuring and onset formation.
O alçamento não assimilatório das vogais /e, o/ pretônicas no português do sul do Brasil: uma abordagem fonológica de contraste e aperfeiçoamento
Authors: Battisti Elisa
Published: January 2025

O artigo trata do alçamento das vogais médias pretônicas /e, o/ não desencadeado por vogal alta seguinte (senhora ~ s[i]nhora, colher ~ c[u]lher) no português de Porto Alegre. A análise baseia-se em Purnell e Raimy (2015), Purnell, Raimy e Salmons (2019), modelo que segue a abordagem de contraste e aperfeiçoamento de Hall (2011) e opera com traços fonológicos privativos, organizados conforme a geometria de traços de Avery e Idsardi (2001). Os objetivos da análise são (i) buscar, na representação fonológica, explicações para as proporções de alçamento observadas, relativamente menores para /e/ do que para /o/, e (ii) representar os contrastes vocálicos do português brasileiro em um modelo com traços privativos pouco explorado na literatura de fonologia do português. A análise mostra que a vogal /o/ é mais suscetível ao alçamento porque é menos marcada do que /e/ no sistema de contrastes da língua. Uma vantagem do modelo usado está em sua estrutura implicacional de traços privativos (gestos), dimensões (contrastes) e níveis superordenados, que explica e restringe a atividade fonológica possível na língua. Uma limitação da análise foi marcar a dimensão Altura da Língua em dois tiers da hierarquia contrastiva, para dar conta dos quatro contrastes de altura do português.
O onset no angolar moderno
Authors: Bandeira Manuele , Alves Ubiratã Kickhöfel
Published: January 2025

Angolar is one of the autochthonous languages of the Republic of São Tomé and Príncipe. This study aims to describe the syllable onset in Angolar, based on Syllable Theory (Selkirk, 1982). As for the corpus, we analyzed 1524 items collected in 2014 and in 2018 in São Tomé and Príncipe, based on recordings with bilinguals (speakers of Angolar as their mother tongue and Portuguese as their second language). Using the Dekereke software (Casali, 2022), we detected the following structures: V, CV, CGV, CCV, CVC, VC and VG. In syllable onset, one or two consonants are legal. This can generate a simple onset (C) or a complex C1C2 sequence with the following configurations: 1) C1 may be an obstruent (b, p, t, d, k, g, f, v) followed by C2 (l, ɾ); 2) C1 may be a consonant (b, p, t, d, k, g, f, v, s) followed by G (w, j). Word-initial nasals followed by obstruents were considered pre-nasalized stops, consisting of a single contour segment in onset position. Furthermore, we highlight that syllable onsets in Angolar follow the Sonority Sequence Principle, as its elements increase in sonority up to the syllable nucleus: C1C2 (0 > 2); and C1G (0 >3).
Diferenças na produção de foco prosódico contrastivo na fala de adultos e de crianças com aquisição fonológica típica e atípica do Português Brasileiro
Authors: Soncin Geovana , Guida Cecília Lorena Silva , Lima Fernanda Leitão de Castro Nunes de , Berti Larissa Cristina
Published: January 2025

The goal of this article is to characterize acoustically and compare prosodic focus marking in speech of adults, children under typical language development and children diagnosed with phonological disorders. Speech samples were obtained from an experiment designed to elicit sentences with contrastive focus and neutral sentences. Acoustical analysis of fundamental frequency, duration and intensity was performed on the sentences produced by each participant’s groups. The results show that groups performed differently in marking contrastive focus by using the three phonetic parameters and suggest that children with phonological disorders may present instabilities in the prosodic plan.
Influence of Worsening Renal Function and Baseline Chronic Kidney Disease on Clinical Outcomes in Patients With Chronic Coronary Syndromes: Insights From the REAL‐CAD Study
Authors: Yoshiki Yu , Ozaki Yukio , Abe Mitsuru , Ismail Tevfik F. , Takahashi Hiroshi , Akao Masaharu , Kawai Hideki , Muramatsu Takashi , Harada Masahide , Ohta Masaya , Hashimoto Yosuke , Shiki Yuichiro , Koshikawa Masayuki , Miyajima Keiichi , Takatsu Hidemaro , Niwa Yudai , Kawashima Naoyuki , Ozaki Reina , Tsuboi Naotake , Iimuro Satoshi , Iwata Hiroshi , Sakuma Ichiro , Nakagawa Yoshihisa , Hibi Kiyoshi , Hiro Takafumi , Fukumoto Yoshihiro , Hokimoto Seiji , Miyauchi Katsumi , Ogawa Hisao , Daida Hiroyuki , Shimokawa Hiroaki , Izawa Hideo , Kimura Takeshi , Nagai Ryozo ,   REAL‐CAD investigators
Published: January 2025

Background

The effect of worsening renal function and baseline chronic kidney disease (CKD) on outcomes in patients with chronic coronary syndrome in the setting of optimal medical therapy remains unknown.

Methods and Results

The REAL‐CAD (Randomized Evaluation of Aggressive or Moderate Lipid Lowering Therapy With Pitavastatin in Coronary Artery Disease) study is a prospective, multicenter, randomized trial of high‐dose (pitavastatin 4 mg/day) or low‐dose (pitavastatin 1 mg/day) statin therapy in 12 118 patients with chronic coronary syndrome. The primary end point was a composite of cardiovascular death, nonfatal myocardial infarction, stroke, or unstable angina requiring hospitalization (major adverse cardiac and cerebral events [MACCE]). CKD was defined as an estimated glomerular filtration rate [eGFR] <60 mL/min per 1.73 m
2
. WRF was defined as a decrease in eGFR ≥20% in the initial year; borderline renal function was an annual decrease of 0%<eGFR<20%, and stable renal function was no decrease. Of 12 118 patients, 4340 had baseline CKD and 7778 did not. The rate of MACCE at 5 years was significantly lower in those without (5.5%) versus with CKD (9.5%) (
P
<0.0001). After excluding 1247 patients who had MACCE, were censored, or missing eGFR within 1 year, 10 871 patients were included. Of these, 3885 were baseline CKD and the remaining 6986 did not have baseline CKD. Of the 10 871 patients, 577 patients had WRF, 6014 patients showed borderline renal function, and the remaining 4280 patients maintained stable renal function. In patients with CKD, WRF was an independent predictor for MACCE at 4 years as compared with stable renal function (hazard ratio [HR]: 1.67; [95% CI, 1.03–2.73;
P
=0.039]). In patients without CKD, borderline renal function was a significant predictor for MACCE at 4 years compared with stable renal function (HR: 1.40 [95% CI, 1.03–1.91;
P
=0.032]).

Conclusions

Baseline CKD was an independent predictor for MACCE in patients with CCS. WRF was a significant predictor for MACCE in patients with CKD. Because borderline renal function was an independent predictor for MACCE even in patients without CKD, mild‐to‐moderate annual declines of eGFR should be carefully monitored (NCT01042730).

Registration

URL:
https://www.clinicaltrials.gov
; Unique Identifier: NCT01042730.
Optimal Duration of Dual Antiplatelet Therapy After Carotid Artery Stenting: A Nationwide Cohort Study
Authors: Yoo Joonsang , Lim Hyunsun , Seo Kwon-Duk
Published: January 2025

BACKGROUND:

Carotid artery stenting (CAS) is an alternative treatment for patients with carotid artery stenosis who are not eligible for carotid endarterectomy. Dual antiplatelet therapy (DAPT) after CAS aims to prevent ischemic stroke. However, its optimal duration remains unclear. We aimed to determine the optimal duration of DAPT by identifying the differences in clinical events that occur depending on the DAPT maintenance period.

METHODS:

Data were obtained from the nationwide database of the Korean Health Insurance Review and Assessment Service between 2007 and 2019. Patients who received CAS, as identified by procedure codes, were divided into 2 groups according to the duration of DAPT (aspirin and clopidogrel): those who maintained DAPT for at least 90 days but for <6 months (short-DAPT group) and those who maintained it for longer (long-DAPT group). The primary outcome was a composite of ischemic stroke, gastrointestinal bleeding, and intracranial hemorrhage within 12 months of switching to single antiplatelet therapy. Statistical analyses used inverse probability of treatment weighting to balance baseline characteristics, with Cox regression and Fine and Gray competing risk models used to assess outcomes.

RESULTS:

Of the 12 034 patients who underwent CAS, 2529 and 9505 were assigned to the short-DAPT and long-DAPT groups, respectively. In the short-DAPT group, ischemic stroke, gastrointestinal bleeding, and intracranial hemorrhage occurred in 41 (1.6%), 22 (0.9%), and 4 (0.2%) patients, respectively. In the long-DAPT group, ischemic stroke, gastrointestinal bleeding, and intracranial hemorrhage occurred in 108 (1.1%), 87 (0.9%), and 4 (0.04%) patients, respectively. The primary outcome did not differ significantly between the groups (2.5% versus 2.1%; adjusted hazard ratio of long-DAPT to short-DAPT, 0.869 [95% CI, 0.652–1.158];
P
=0.337).

CONCLUSIONS:

Short-duration DAPT can be recommended, as it does not differ from long-duration DAPT in terms of clinical efficacy and adverse events after CAS.
Runtime Analysis of Typical Decomposition Approaches in MOEA/D for Many-Objective Optimization Problems
Authors: Huang Zhengxin , Zhou Yunren , Chen Zefeng , Dang Qianlong
Published: January 2025

Decomposition-based multi-objective evolutionary algorithms (MOEAs) are popular methods utilized to address many-objective optimization problems (MaOPs). These algorithms decompose the original MaOP into several scalar optimization subproblems, and solve them to obtain a set of solutions to approximate the Pareto front (PF). The decomposition approach is an important component in them. This paper presents a runtime analysis of a MOEA based on the classic decomposition framework using the typical weighted sum (WS), Tchebycheff (TCH), and penalty-based boundary intersection (PBI) approaches to obtain an optimal solution for any subproblem of two pseudo-Boolean benchmark MaOPs, namely mLOTZ and mCOCZ. Due to the complexity and limitation of the theoretical analysis techniques, the analyzed algorithm employs one-bit mutation to generate offspring individuals. The results indicate that when using WS, the analyzed algorithm can consistently find an optimal solution for every subproblem, which is located in the PF, in polynomial expected runtime. In contrast, the algorithm requires at least exponential expected runtime (with respect to the number of objectives m) for certain subproblems when using TCH or PBI, even though the landscapes of all objective functions in the two benchmarks are strictly monotone. Moreover, this analysis reveals a drawback of using WS: the optimal solutions obtained by solving subproblems are more easily mapped to the same point in the PF, compared to the case of using TCH. When using PBI, a smaller value of the penalty parameter is a good choice for faster convergence to the PF but may compromise diversity. To further understand the impact of these approaches in practical algorithms, numerical experiments on using bit-wise mutation to generate offspring individuals are conducted. The findings of this study may be helpful for designing more efficient decomposition approaches for MOEAs in future research.
Weathering Changes: Livelihood Adaptation to Weather Shocks in Rural India by Disadvantaged Social Groups
Authors: Das Dhiman
Published: January 2025

In this article, we examine how households from disadvantaged social groups in India adapt through migration to climate-related shocks. We examine the relative importance of factors like social networks and public intervention in enabling adaptation to slow-onset climate change. We use household- and village-level data from two consecutive waves of the Indian Human Development Survey and gridded weather data from CRU at the University of East Anglia for our analysis. Our results indicate that, in India, major changes in dryness significantly increase migration, but disadvantaged social groups facing climate change are less likely to migrate. Social networks do not play any significant role in the migration behaviour of disadvantaged groups facing these changes. Efficient implementation of poverty alleviation programmes does improve the probability of migration among these groups.

JEL Codes: O15, Q54
“A Double Decline in Character”: A Grounded Theory Analysis of Female Drug User Experiences in Iran
Authors: Momeni Alireza , Hellman Matilda , Ghiabi Maziyar
Published: January 2025

Using a constructivist grounded theory design, this study explores the perception and experience of Iranian women living with drug use, identifying everyday conflicts and coping strategies that enable them to manage their situation. We conducted unstructured, in-depth interviews with abstinent drug users (11) and healthcare professionals (2) at three rehab centers in Tehran, Iran. In line with our grounded theory aspirations to explore the social meanings of women's drug use and addiction, we supplemented the interviews with a surrounding material consisting of articles published in the main national newspaper from 2015 to 2018 and a film documentary (10 parts, 3 h) entitled “Iranian Women of Addiction,” ( Shab boohay-e-sokhteh) (2010–2011). Our analysis resulted in two main bundles of meaning-making that we claim are permeating the everyday lives of Iranian women with drug use: the double decline in character, and self-shielding. The study reveals the simultaneous presence of two stigmatized identities: drug use and sex work ( fahsha). It shows that the stigma of sex work is closely connected to a drug-related identity, irrespective of whether women are actively involved in sex work or not. The findings illustrate how societal views are biased against drug user women in the domain of drug use, diminishing their presence and voice. The interviewees tried to manage by developing a peer network, adopting a protective role, and becoming intrinsically motivated to quit drug use. The study furthers our understanding of women's alarming and complex realities in traditional Islamic and familistic patriarchal structures.
Aging With or Aging Out of Drug Use? Older Adults’ Experiences of Aging with Long-Term Drug Use
Authors: Liahaugen Flensburg Olivia , Richert Torkel , Alftberg Åsa
Published: January 2025

Older adults with long-term drug use have long been overlooked in both drug research and aging research. More knowledge is needed about their experiences and needs. Drug use is often seen as a youth phenomenon and as something that with time leads to destructiveness and compulsion. A more nuanced picture of who uses drugs and what the use may look like over time is necessary. There is limited insight into what it means to age with drug use, based on individuals’ own stories and experiences. We conducted 27 semistructured interviews in Sweden with individuals aged 55 or older who reported current and long-term drug use. In this article, we demonstrate how the relationship with drugs evolves over time and how the interviewees contemplate stopping or continuing their use. Three themes were identified: (1) Aging out of drug use: Thoughts on drug cessation. Some expressed a desire to end their drug use. The reasons behind this varied, but there was a clear pattern related to older age. (2) Aging with drug use: Thoughts on continued use. Some had a desire to continue using drugs and expressed concern about how everyday life would be without them. (3) Age adapted drug use: A change in drug use. Several participants stated that their drug consumption had changed over time and with age. Drugs no longer dominated their lives as before but still served essential functions. The themes should not be seen as rigid categories, but as fluid narratives. Understanding this variation provides a deeper insight into people's often complex relationship with drugs.
Effectiveness of ChatGPT in facilitating learning for students with special educational needs: An empirical study in Saudi Arabia
Authors: Alsahli Mohammed , Alanezi Fahad , Sh. Basri Wael , Attar Razaz Waheeb , Alghamdi Alya , Alyahya Norah Mohammed , Albagmi Salem , Almutairi Saud Asman , Alsedrah Ibrahim Tawfeeq , Arif Wejdan M , Alsadhan Abeer Abdullah , AlShammary Miznah Hizam , Bakhshwain Amal Mubarak , almuhanna Afnan fahd , Alnaim Norah , Alhazmi Amal Hassan
Published: January 2025

Study purpose

This paper aims to explore the effectiveness of ChatGPT in facilitating learning for medical students with special educational needs (SEN) while acknowledging and addressing the challenges that SEN students may encounter in utilizing this technology.

Methods

This cross-sectional survey study assessed ChatGPT's efficacy in supporting medical students with SEN across three Saudi Arabian universities. Utilizing purposive and convenience sampling, a questionnaire was administered to 283 SEN students. Statistical analyses, including t-tests and ANOVA, were conducted to evaluate perceptions of ChatGPT's effectiveness, considering demographic factors and impairment types.

Results

Notable differences were observed in perceptions of ChatGPT's effectiveness by impairment type and education level. Statistically significant differences were observed among the participants with different types of impairments in relation to flexibility in communication ( p = .01), scaffolding and guided practice ( p = .0435), immediate feedback and reinforcement ( p = .0334), visual and audio support ( p = .0244), and simplified learning ( p = .002) factors. For instance, individuals with communication and interaction impairments rated ChatGPT's support significantly higher for simplified learning ( M = 4.39, p = .002) and visual/audio support ( M = 4.08, p = .024) compared to other impairments. Education level significantly influenced perceptions across all support factors ( p < .05), with diploma holders consistently rating ChatGPT more favorably.

Conclusion

Although by providing personalized, simplified, and scaffolded learning experiences, along with social and emotional support, ChatGPT demonstrates promising potential in enhancing learning of SEN students; it does not prove to be effective across all types of impairments.