bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatio-temporal analysis of a digital Trail Making Test part-A can evaluate cognitive dysfunctions in elderly rehabilitation inpatients
Authors: Kubo Kouki , Hama Seiji , Furui Akira , Mizuguchi Tomohiko , Yanagawa Akiko , Kandori Akihiko , Sakai Hiroto , Morisako Yutaro , Orino Yuki , Hamai Maho , Fujita Kasumi , Yamawaki Shigeto , Tsuji Toshio 
Published: April 2023

Abstract
We examined a newly developed digitized Trail Making Test using an iPad (iTMT) as a brief of cognitive function screening test. We found that the iTMT part-A (iTMT-A) can estimate generalized cognitive function in elderly rehabilitation inpatients examined using the Mini-Mental State Examination (MMSE). Forty-two hospitalized participants undergoing rehabilitation (rehab participants), 30 of whom had cerebral infarction/hemorrhage (stroke participants), performed the iTMT three times and the MMSE. Each iTMT-A trial’s completion time was divided into the move and dwell times, for which the deviations in the left-right, forward-backward, or diagonal direction or position were also calculated. In stepwise analysis, the power of estimating the MMSE score was increased by using the dwell and move times with the deviation quadrant extracted from the iTMT-A, even for subjects with low MMSE scores. Moreover, the use of data from repeated iTMT-A trials reduced the error and improved the estimation ability. The final remaining factors included factors associated with physical disability of upper limbs and the cerebral lesion side. The iTMT-A extracts significant factors temporally and spatially, and by incorporating the learning effect of repeated trials, it may be possible to screen cognitive and physical functions for rehabilitation patients, including elderly or stroke patients.
Sentiment Analysis for Social Media Big Data utilizing Advanced Hybrid Deep Learning Algorithms
Authors: Ahmed Hamdan , Aljuboori Fadhil 
Published: April 2023

Abstract

With the increase in the use of social media sites significantly and the enlarge in the users number as they provide all the basic services and daily requirements of customers for most vital activities at all levels of commercial, social, marketing, educational and others, there is an urgent need to provide a comprehensive analytical and predictive system that works on reading and analyzing the desires of users to give a comprehensive description It facilitates searches and shortens effort, time, storage and search spaces for your servers and customers alike. In this study, three data sets have been considered and tested using sentiment analysis with optimization technique convolutional neural network (CNN), hyper parameters optimized Tree Structured Parzen Estimator with LSTM, and hybrid CNN with Groo, hyper parameters optimization using Tree Structured Parzen Estimator (TPE), and Define by Run deep learning algorithms utilizing Jupiter Python programming language. The data sets represent big data for Amazon social media containing information with different classes, items, and attributes. The classification of the analyzed data will produce a recommender system that simplify the selection process for customers and users of social networking sites by providing readings and analyzes of various types of information circulated on different types of websites, so that the information is trained as a supervisory training for various tweets by collecting different customers information to predict their various interests and needs.
Visual-attentional and phonological deficits explored in French dyslexic students: eye movements recorded during a phonological lexical decision task
Authors: Premeti Aikaterini , Isel Frédéric , Bucci Maria Pia 
Published: April 2023

Abstract
Whether dyslexia is a phonological or a visual attention problem remains a widely debated issue. This study aimed to compare the eye movements of 32 French university students with and without dyslexia while performing a phonological lexical decision task on 300 visually presented stimuli. Stimuli involved either a lexical (i.e., words) or a non-lexical route relying on a grapheme-phoneme correspondence (pseudohomophones and pseudowords), while others involved only a visual search (consonant and symbol sequences). We recorded the number and the duration of single and double fixations and the number and amplitude of the first saccade made on the stimuli. Compared to controls, dyslexics made fewer single than double fixations during reading regardless of the type of stimulus (lexical and non-lexical), while the number and the amplitude of the first saccade was similar in the two groups of participants. Taken together, these results suggest that both visual and phonological impairments may be observed in dyslexia and support the hypothesis that dyslexia is a multifactorial deficit.
Complex Modulus characterization of an optimized binder with SCMs: proposition of an enhanced cement formulation to improve stiffness behaviorand durability of mortars and concretes
Authors: Targino Daniel Lira Lopes , Holanda Ana Dulce de Castro , Henriquez Pablo Andrade Martinez , Freitas Ingrid Lourrany Barreto , Boukhelf Fouad , Mendili Yassine El , Babadopulos Lucas Feitosa de Albuquerque Lima 
Published: April 2023

Abstract
Materials optimization is an aspect of continuous endeavor for civil engineering in many applications, especially in construction where the materials’ durability and mechanical performance are crucial for structural integrity. Structures such as aerogenerators, both towers and foundations, are highly susceptible to cyclic loads with a broad range of frequencies and levels. The improvement of the stiffness behavior can significantly enhance their fatigue resistance and consequently durability. This paper aims to evaluate the impact of a high-performance binder optimization, using supplementary cementitious materials (SCMs) to improve the mechanical behavior of mortars and concretes, by improving stiffness response under dynamic loading, which is related to durability and fatigue life-service. Static tests (axial compressive and splitting tensile strengths) were conducted as well as cyclic stiffness tests that were proposed as a new methodology for these kinds of materials, that may better relate to dynamic behavior in field. The proposition consists of testing complex modulus tests under sinusoidal loading either in pure compression or in pure tension, adopting low (0.1 Hz to 1 Hz) and mid-range (1 Hz to 25 Hz) loading frequencies. The results show that the optimized binder resulted in a superior material with up to 23% stiffer loading response and 13.8% more energy storage elastically, with also inferences on improved durability, which is expected to delay pathological manifestations. The proposed testing protocol obtained results compatible with the literature and seems applicable for evaluating the dynamic behavior of cementitious materials.
Temperature and pH responsive behavior of wormlike micelles formed by a long chain Gemini-like surfactant
Authors: Pei Xiaomei , Pan Ting , Han Xu , Yan Yiqun , Wu Junhui , Song Binglei , Chen Zhao , Gu Yao 
Published: April 2023

Abstract
A Gemini-like surfactant is formed by connecting short chain dibasic acid and long chain tertiary amine in the molar ratio of 1:2 through the non-covalent action of electrostatic attraction, and does not need complicated synthesis. Due to the tertiary amine group in the Gemini-like surfactant, it exhibits pH-responsive properties. However, in the research, we were pleasantly surprised to find that the Gemini-like surfactants also showed temperature response characteristics. With the increase of temperature, the viscosity of the system increases rapidly, and it is resistant to high temperatures. At 60°C, the zero-shear viscosity of the system at the concertation of 300 mM can reach an extremely high value of 11967.73 Pa·s, which was higher than most of wormlike micelles formed by the conventional covalently linked oligomeric counterparts. The reason for this phenomenon may be that as the temperature increases, the hydrogen bonds in the system are destroyed, resulting in the reduction of the repulsive force between molecules and the shortening of the intermolecular distance, which makes the micelles more entangled closely.
Deforestation as a site of conflict and differentiation: The case of the Rohingya refugee influx in Teknaf
Authors: Ahmed Tasfia , Sabastini Priyong 
Published: April 2023

Abstract

The migration of refugees and displaced persons has previously been linked to deforestation globally, with reports of clashes over resources and forest rights being associated with it. This paper aims to qualitatively study the aforementioned phenomenon through the case of deforestation associated with the Rohingya refugee influx in Bangladesh, which has resulted in the deforestation of over 8,000 acres of forest land. The deforestation has reportedly led to various livelihood issues for host community members including difficulty in conducting animal husbandry, agroforestry and the ability to forage for food. This paper aims to look into the social aspects of the effects of deforestation on host community Bangladeshis, by studying whether or not its impact has resulted in raising inequalities or vulnerabilities between host community groups based on their ethnicity and/or socio-economic positioning. Additionally, this paper aims to analyse the effects of deforestation on the cohesion between the host community Bangladeshis and Rohingya refugees and relations between different host community groups as well. The data of this study has been gathered through five focus group discussions which incorporated 35 forest-dependent host community members, and six key informant interviews consisting of middle-class development workers, politicians and journalists. This study indicates that the impact of deforestation may have disproportionately affected marginalised groups, especially in terms of agroforestry and animal husbandry. Findings additionally illustrate that the resulting effects of deforestation may have negatively influenced the cohesion between host community members and Rohingya refugees, while contributing to tension between farmers and relatively powerful groups who utilised land shortages after the influx.
Talbot effect for the third order Lugiato-Lefever equation
Authors: Cho Gunwoo , Kim Seongyeon , Seo Ihyeok 
Published: April 2023

Abstract
We discuss the Lugiato-Lefever equation and its variant with third-order dispersion, which are mathematical models used to describe how a light beam forms patterns within an optical cavity. It is mathematically demonstrated that the solutions of these equations follow the Talbot effect, which is a phenomenon of periodic self-imaging of an object under certain conditions of diffraction. The Talbot effect is regarded as the underlying cause of pattern formation in optical cavities.
2020 Mathematics Subject Classification. Primary: 35B45; Secondary: 35B10.
Investigating the cecal microbiota of broilers raised in extensive and intensive production systems
Authors: Marcolla Camila S. , Ju Tingting , Lantz Hannah L. , Willing Benjamin P. 
Published: April 2023

Abstract
Background Intensive broiler production practices are structured to prevent the introduction and spread of pathogens; however, they can potentially minimize the exposure of broilers to beneficial commensal bacteria. In this study, we used 16s rRNA amplicon sequencing to perform a large-scale characterization of the cecal microbiota of 35-day-old broilers from intensive production systems (IPS) and from extensive production systems (EPS), aiming to determine which microbes are normal inhabitants of the broiler ceca and which microbes might be missing from broilers in IPS. In addition, we generated a collection of bacterial isolates to be used as a resource to further explore the effects of selected isolates on bird physiology, and to elucidate the role of individual bacterial species within the cecal microbial community.Results Our results indicated major differences in the microbiota of broilers between systems: the microbiota of broilers from EPS was dominated by Bacteroidetes, whereas Firmicutes dominated the microbiota of broilers from IPS. A number of bacterial taxa ubiquitous in the EPS microbiota were shown to be infrequent or absent from the IPS microbiota, and the EPS microbiota presented higher phylogenetic diversity and greater predicted functional potential than that of broilers in IPS.Conclusions In the current study, we identified Olsenella, Alistipes, Bacteroides, Barnesiella, Parabacteroides, Megamonas, and Parasutterella as core bacteria within the broiler microbiota that seem to be depleted in broilers from IPS, which could be further investigated for their effects on bird physiology and potential application as next-generation probiotics.
Spatial distribution, formation mechanism, and health risk assessment of high-fluoride groundwater at the largest antimony mine in Hunan Province, China
Authors: Wang Yantang , Hao Chunming , He Kaikai , Peng Yingao , Sun Ximeng , Liu Min 
Published: April 2023

Abstract
To date, few systematic studies of the spatial distribution, formation mechanism, and health risks of high-fluoride (F−) shallow groundwater in humid and semi-humid areas of the Xikuangshan antimony mine, Hunan Province, China. In this study, during March and April 2022, a total of 39 shallow groundwater samples were collected and analyzed using factor analysis, principal component analysis, and health risk assessment. F− concentrations in the shallow groundwater were found to range from 0.08 to 15.00 mg/L (mean: 1.21 mg/L), with 25.64% of the samples having F− concentrations higher than in the Chinese national standard for drinking water (1.00 mg/L). Principal component analysis revealed that the main source of F− in the shallow groundwater samples is cation exchange, accounting for 73.40%, followed by the dissolution and precipitation of F-bearing minerals (15.10%), and human influence (11.50%). Among different age groups, children had the highest percentage of individuals (36.38%) with an F− intake above the health risk quotient safety limit, followed by adult males (23.12%), teenagers (22.21%), and infants (21.22%). The findings of this study will contribute to devising strategies for the provision of safe drinking water and management of the geological environment.
Pre-Treatment CT Radiomics and Clinical Factors Predict Malignant Esophageal Fistula in Patients with Esophageal Cancer
Authors: Zhu Chao , Sun Wenju , Chen Cunhai , Qiu Qingtao , Wang Shuai , Song yang , Ma Xuezhen 
Published: April 2023

Abstract
Background
Malignant Esophageal fistula (MEF), which occurs in 5–15% of esophageal cancer (EC) patients, has a poor prognosis, and patients eventually die of nutritional failure, chest infection, mediastinal abscess, or great vessel injury in a short period of time. As a result, stratification of the high-risk group and intervention to prevent the occurrence is critical. The goal of this study was to build and validate a model to predict the occurrence of esophageal fistula in EC patients.
Methods
Fifty-three patients with MEF and 69 controls were randomly assigned to a training cohort (n = 86) and a validation cohort (n = 36). To identify clinically independent predictors, logistic univariate and multivariate regression analyses were used. Radiomic features were extracted from pre-treatment CT, which were then screened using least absolute shrinkage and selection operator (Lasso) regression. A clinical nomogram based on clinical risk factors, a predictive model based on radiomic features, and a nomogram incorporating the radiomic signature and clinical independent predictors were developed. The models were validated and compared by discrimination, calibration, reclassification, and clinical benefit.
Results
Univariate analysis identified clinical risk factors including stenosis, gender, and T stage. In multivariate analysis, stenosis was found to be an independent predictor (P = 0.023). A clinical nomogram was developed that included stenosis, gender, and T stage. A radiomic signature was created by ten features selected from 851 radiomic features extracted from pre-treatment CT images using Lasso regression. In discrimination, caliberation curve, and decision curve analysis, the joint nomogram incorporating clinical factors and radiomic signature outperformed the clinical nomogram and radiomics predictive model. When compared to the clinical nomogram, the radiomics-clinical prediction nomogram improved NRI by 0.236 (95%CI: 0.153,0.614) and IDI by 0.125 (95%CI: 0.040,0.210), P = 0.004.
Conclusion
We developed and validated the first radiomics-clinical nomogram for malignant esophageal fistula, which could assist clinicians in identifying patients at high risk of MEF.
Cognition of Abdominal Pain and Abdominal Discomfort in Patients with Irritable Bowel Syndrome with Diarrhea of China
Authors: Lu Jia , Chen Yang , Shi Lili , Li Xiaoqing , Fei Guijun , Li Ji , Yang Aiming , Fang Xiucai 
Published: April 2023

Abstract
Background In Asia, the proportion of patients with irritable bowel syndrome (IBS) with abdominal discomfort alone is significantly higher than that in western countries. The purpose of this study is to understand the cognition of abdominal pain and abdominal discomfort in patients with IBS in China, and to compare the clinical characteristics of patients with abdominal pain alone and abdominal discomfort alone.Methods Patients with IBS with diarrhea (IBS-D) who met Rome III diagnostic criteria and had episodes of at least one day/week were consecutively enrolled. The cognition of abdominal pain and abdominal discomfort were investigated through face-to-face unstructured interview. Patients were divided into pain group and discomfort group according to the cognition interviews, then the characteristics and severity of symptoms (IBS symptom severity scale, IBS-SSS), IBS quality of life (IBS-QOL) and psychological state were compared between groups.Results A total of 88 patients with IBS-D were enrolled. Most of the patients with self-reported abdominal pain described pain as spasm/cramping; patients with self-reported abdominal discomfort had as many as 24 kinds of descriptions to report their discomfort. Most patients having abdominal pain and discomfort could accurately distinguish the two symptoms. The degree of abdominal pain in pain group was higher than abdominal discomfort in discomfort group (P = 0.002). There was no significant difference in IBS-SSS, extra-intestinal pain, IBS-QOL, and scores of HAMA and HAMD between the two groups.Conclusions For Chinese patients with IBS-D, abdominal pain and abdominal discomfort are two different symptoms, but they have similar clinical features.Trial registration ChiCTR, ChiCTR1900028082. Registered 11 December 2019 - Retrospectively registered, http://www.chictr.org.cn
Changes in the severity of chemotherapy-induced nausea and vomiting according to the menopausal stage of breast cancer patients during adjuvant chemotherapy: A prospective observational study
Authors: Yeom Chan-Woo , Lee Sangil , Lee Seonmi , Son Kyung-Lak , Lee Kwang-Min , Kim Won-Hyoung , Kim Tae-Yong , Im Seock-Ah , Lee Kyung-Hun , Hahm Bong-Jin , Jung Dooyoung 
Published: April 2023

Abstract
Purpose Breast cancer has been reported to be common in middle-age, but little is known about the relationship between menopausal stage and the severity of chemotherapy-induced nausea and vomiting (CINV) in breast cancer patients. Therefore, we examined the association between menopausal stage and CINV severity.Methods Participants were prospectively enrolled from a tertiary general hospital. We evaluated CINV severity of 187 breast cancer patients receiving adjuvant chemotherapy, using a Likert scale from 1 to 10, before chemotherapy (W0), 4 weeks after the first chemotherapy (W4), and 12 weeks (W12) after the first chemotherapy. Premenopause, perimenopause, and postmenopause period were classified by age 45 and 55 years, respectively. CINV severity at different time-points and change values in CINV severity (cCIN, cCIV) at each time point, relative to W0, were compared using a linear mixed modelResults Significant group-by-time interactions were observed for CIN (p = 0.011), CIV (p = 0.027), and cCIN (p = 0.030). In postmenopausal period women, unlike in premenopausal and perimenopausal period women, the mean change values for CIN and CIV at each time point relative to W0 were not significantly different. In the post-hoc analysis, there was a significant difference (p = 0.007) in cCIN at W4 between perimenopausal and postmenopausal period women.Conclusions Changes in CINV severity in breast cancer patients follow different patterns according to menopausal stage. Perimenopausal period women seem to be particularly susceptible to CINV. During chemotherapy, it is necessary to manage CINV with consideration of menopausal stage.
BayesDLMfMRI: an R package for task-based fMRI modeling based on Bayesian matrix-variate dynamic linear models
Authors: Jiménez Johnatan Cardona , Pérez Carlos , Ramírez Isabel 
Published: April 2023

Abstract
Background: Functional magnetic resonance imaging (fMRI) is a technique that has caught the attention of scientists since its appearance over thirty years ago. This tool allows for analyzing human brain activity through a sequence of magnetic resonance (MR) images. One important stage in the application of the fMRI technique is the statistical analysis of the sequence of post-processed images. The General Linear Model (GLM) is perhaps the most common statistical model applied for task-based fMRI analysis. However, in the majority of applications where this model is used, the spatiotemporal structures usually present in this type of data are commonly ignored. Thus, in the package introduced in this article, we have implemented a statistical method based on Matrix-Variate Dynamic Linear Models (MDLM) that allows taking into account the spatiotemporal structures in the modeling of task-based fMRI data.
Results: The BayesDLMfMRI package performs statistical analysis for task-based fMRI data at both individual and group levels. The analysis to detect brain activation at the individual level is based on modeling the fMRI signal using MDLM. The analysis for the group stage is based on posterior distributions of the state parameter obtained from the modeling at the individual level. In this way, this package offers several R functions with different algorithms to perform inference on the state parameter to assess brain activation for both individual and group stages. Those functions allow for parallel computation when the analysis is performed for the entire brain as well as analysis at specific voxels when it is required.
Conclusions: In summary, we present a software implementation of a well-tested statistical method for task-based fMRI analysis that would complement analysis performed with more popular packages such as FSL and SPM.