bluuebunny/crossref_metadata_2025_split huggingface dataset:
Stochastic geometry models for texture synthesis of machined metallic surfaces: sandblasting and milling
Authors: Jeziorski Natascha , Redenbach Claudia 
Published: August 2024

AbstractTraining defect detection algorithms for visual surface inspection systems requires a large and representative set of training data. Often there is not enough real data available which additionally cannot cover the variety of possible defects. Synthetic data generated by a synthetic visual surface inspection environment can overcome this problem. Therefore, a digital twin of the object is needed, whose micro-scale surface topography is modeled by texture synthesis models. We develop stochastic texture models for sandblasted and milled surfaces based on topography measurements of such surfaces. As the surface patterns differ significantly, we use separate modeling approaches for the two cases. Sandblasted surfaces are modeled by a combination of data-based texture synthesis methods that rely entirely on the measurements. In contrast, the model for milled surfaces is procedural and includes all process-related parameters known from the machine settings.
A theory-informed deep learning approach to extracting and characterizing substance use-related stigma in social media
Authors: Roesler David , Johnny Shana , Conway Mike , Chen Annie T. 
Published: August 2024

Abstract
Background
Stigma surrounding substance use can result in severe consequences for physical and mental health. Identifying situations in which stigma occurs and characterizing its impact could be a critical step toward improving outcomes for individuals experiencing stigma. As part of a larger research project with the goal of informing the development of interventions for substance use disorder, this study leverages natural language processing methods and a theory-informed approach to identify and characterize manifestations of substance use stigma in social media data.

Methods
We harvested social media data, creating an annotated corpus of 2,214 Reddit posts from subreddits relating to substance use. We trained a set of binary classifiers; each classifier detected one of three stigma types: Internalized Stigma, Anticipated Stigma, and Enacted Stigma, from the Stigma Framework. We evaluated hybrid models that combine contextual embeddings with features derived from extant lexicons and handcrafted lexicons based on stigma theory, and assessed the performance of these models. Then, using the trained and evaluated classifiers, we performed a mixed-methods analysis to quantify the presence and type of stigma in a corpus of 161,448 unprocessed posts derived from subreddits relating to substance use.

Results
For all stigma types, we identified hybrid models (RoBERTa combined with handcrafted stigma features) that significantly outperformed RoBERTa-only baselines. In the model’s predictions on our unseen data, we observed that Internalized Stigma was the most prevalent stigma type for alcohol and cannabis, but in the case of opioids, Anticipated Stigma was the most frequent. Feature analysis indicated that language conveying Internalized Stigma was predominantly characterized by emotional content, with a focus on shame, self-blame, and despair. In contrast, Enacted Stigma and Anticipated involved a complex interplay of emotional, social, and behavioral features.

Conclusion
Our main contributions are demonstrating a theory-based approach to extracting and comparing different types of stigma in a social media dataset, and employing patterns in word usage to explore and characterize its manifestations. The insights from this study highlight the need to consider the impacts of stigma differently by mechanism (internalized, anticipated, and enacted), and enhance our current understandings of how each stigma mechanism manifests within language in particular cognitive, emotional, social, and behavioral aspects.
Deep-Transfer-Learning–Based Natural Language Processing of Serial Free-Text Computed Tomography Reports for Predicting Survival of Patients With Pancreatic Cancer
Authors: Kim Sunkyu , Kim Seung-seob , Kim Eejung , Cecchini Michael , Park Mi-Suk , Choi Ji A , Kim Sung Hyun , Hwang Ho Kyoung , Kang Chang Moo , Choi Hye Jin , Shin Sang Joon , Kang Jaewoo , Lee Choong-kun 
Published: August 2024

PURPOSE To explore the predictive potential of serial computed tomography (CT) radiology reports for pancreatic cancer survival using natural language processing (NLP). METHODS Deep-transfer-learning–based NLP models were retrospectively trained and tested with serial, free-text CT reports, and survival information of consecutive patients diagnosed with pancreatic cancer in a Korean tertiary hospital was extracted. Randomly selected patients with pancreatic cancer and their serial CT reports from an independent tertiary hospital in the United States were included in the external testing data set. The concordance index (c-index) of predicted survival and actual survival, and area under the receiver operating characteristic curve (AUROC) for predicting 1-year survival were calculated. RESULTS Between January 2004 and June 2021, 2,677 patients with 12,255 CT reports and 670 patients with 3,058 CT reports were allocated to training and internal testing data sets, respectively. ClinicalBERT (Bidirectional Encoder Representations from Transformers) model trained on the single, first CT reports showed a c-index of 0.653 and AUROC of 0.722 in predicting the overall survival of patients with pancreatic cancer. ClinicalBERT trained on up to 15 consecutive reports from the initial report showed an improved c-index of 0.811 and AUROC of 0.911. On the external testing set with 273 patients with 1,947 CT reports, the AUROC was 0.888, indicating the generalizability of our model. Further analyses showed our model's contextual interpretation beyond specific phrases. CONCLUSION Deep-transfer-learning–based NLP model of serial CT reports can predict the survival of patients with pancreatic cancer. Clinical decisions can be supported by the developed model, with survival information extracted solely from serial radiology reports.
Sex-specific Associations of Aldosterone and Renin With Body Composition: A Population-based Cohort Study
Authors: Hundemer Gregory L , Agharazii Mohsen , Madore François , Piché Marie-Eve , Gagnon Claudia , Bussières Alexandra , St-Jean Matthieu , Leung Alexander A , Kline Gregory A , Sood Manish M , Burger Dylan , Ramsay Tim , Goupil Rémi 
Published: August 2024

Abstract

Context
Renin–angiotensin–aldosterone system (RAAS) activation is closely linked to obesity; however, the sex-specific associations between RAAS activity and body composition among individuals without obesity are not well understood.

Objective
To investigate the associations of aldosterone and renin with body composition according to sex in the general population.

Design
Population-based cohort study.

Setting
Québec (Canada).

Participants
Adults aged 40 to 69 years enrolled in CARTaGENE between 2009 and 2010 (N = 3687).

Exposures
Plasma aldosterone and renin concentrations.

Main Outcome Measures
Body composition assessed via anthropometrics (waist circumference and waist-to-hip ratio), bioelectrical impedance (lean body mass, fat mass, and muscle mass), and cardiac magnetic resonance imaging (epicardial and pericardial adipose tissue volumes).

Results
The mean (SD) age and body mass index were 55 (8) years and 27.3 (4.8) kg/m2, respectively. Among males, higher aldosterone and renin were associated with increased waist circumference, increased waist-to-hip ratio, increased fat mass, decreased lean body mass, and decreased muscle mass (P &lt; .05). Aldosterone (P = .02), but not renin (P = .43), was associated with increased ectopic cardiac adiposity in males. In contrast, higher renin (P &lt; .05), but not aldosterone (P ≥ .05), was associated with increased waist circumference, increased waist-to-hip ratio, and increased cardiac adiposity in females. Among females, higher renin and aldosterone were associated with increased fat mass (P &lt; .05) but were not associated with lean body mass or muscle mass (P ≥ .05). All aforementioned associations were independent of body weight.

Conclusion
Independent of body weight, increased RAAS activity is associated with unfavorable differences in body composition; however, the strength and pattern of association varies by sex.
Starvation Ketoacidosis in Pregnancy: An Unusual Presentation and Brief Literature Review
Authors: Abraham Lisa , Ning Xinyuan , Whitlatch Hilary B 
Published: August 2024

Abstract
Starvation ketoacidosis in pregnant patients is a rare but life-threatening condition that requires prompt diagnosis and timely treatment. A 35-year-old pregnant woman at 33 weeks’ gestation was admitted for abdominal pain with poor oral intake. She was diagnosed with perforated appendicitis and underwent emergent laparotomy. During the procedure and afterwards, she was found to have an anion gap metabolic acidosis. She was treated with a dextrose infusion with a fixed-rate insulin with correction of metabolic parameters. Women in late pregnancy are at increased risk for ketosis from increased relative insulin resistance and enhanced lipolysis. There is no consensus on optimal management of starvation ketoacidosis of pregnancy; however, carbohydrate administration is a cornerstone of treatment. We chose simultaneous administration of carbohydrates with insulin to overcome any inherent insulin resistance and to suppress lipolysis with rapid resolution of the patient's metabolic derangements.
I segnali discorsivi interazionali nel parlato di bambini plurilingui.
Authors: Salzmann Katharina , Videsott Ruth 
Published: August 2024

The aim of this paper is to investigate the use of interactional pragmatic markers in a multilingual corpus of child language in the Ladin valleys in South Tyrol (Italy). It has been argued that in contact-induced contexts speakers tend to prefer the set of elements of the pragmatically dominant language, in order to reduce the cognitive pressure they are exposed to, in particular in a minority language (cf. Matras 2000). Yet, very little is known about the use of pragmatic markers in child language, even though the pragmatic competence, i. e. the appropriate use of language as well as the proper realization of speech acts in a particular situational context, is one of the key competences children need to acquire during the language acquisition process. The present study was carried out within the sociolinguistic framework of the Ladin valleys, which is characterized by a varied multilingualism on the institutional level and in family contexts. The corpus contains approximately eight hours of spoken data from eight children aged three to six across the three official languages Ladin, German and Italian. This work aims at analysing the micro-functions of interactional pragmatic markers and at investigating how the use of these elements is linked to the linguistic and cognitive development of preschool children. It also contributes to the study of contact-induced phenomena that emerge in a multilingual context.
Neurocognitive effects of 3 mA prefrontal electrical stimulation in schizophrenia: A randomized sham-controlled tDCS-fMRI study protocol
Authors: Hallajian Amir-Homayun , Sharifi Kiomars , Rostami Reza , Saeed Fahimeh , Mokarian Rajabi Shirin , Zangenehnia Negin , Amini Zahra , Askari Zahra , Vila-Rodriguez Fidel , Salehinejad Mohammad Ali 
Published: August 2024

Background
Schizophrenia (SCZ) is characterized by cognitive deficits that are linked to prefrontal cortex dysfunction. While transcranial direct current stimulation (tDCS) shows promise for improving cognition, the effects of intensified 3mA tDCS protocols on brain physiology are unknown. This project aims to elucidate the neurophysiological and cognitive effects of an intensified prefrontal tDCS protocol in SCZ.

Methods
The study is designed as a randomized, double-blind, 2-arm parallel-group, sham-controlled, trial. Forty-eight participants with SCZ and cognitive impairment (measured via a set of executive functions tests) will be randomly allocated to receive either a single session of active (n = 24) or sham (n = 24) tDCS (20-min, 3-mA). The anodal and cathodal electrodes are positioned over the left and right DLPFC respectively. The stimulation occurs concurrently with the working memory task, which is initiated precisely 5 minutes after the onset of tDCS. Structural and resting-state (rs-fMRI) scans are conducted immediately before and after both active and sham tDCS using a 3 Tesla scanner (Siemens Prisma model) equipped with a 64-channel head coil. The primary outcome will be changes in brain activation (measures vis BOLD response) and working memory performance (accuracy, reaction time).

Discussion
The results of this study are helpful in optimizing tDCS protocols in SCZ and inform us of neurocognitive mechanisms underlying 3 mA stimulation. This study will additionally provide initial safety and efficacy data on a 3 mA tDCS protocol to support larger clinical trials. Positive results could lead to rapid and broader testing of a promising tool for debilitating symptoms that affect the majority of patients with SCZ. The results will be made available through publications in peer-reviewed journals and presentations at national and international conferences.
Introducing effective genes in lymph node metastasis of breast cancer patients using SHAP values based on the mRNA expression data
Authors: Vahed Sepideh Zununi , Khatibi Seyed Mahdi Hosseiniyan , Saadat Yalda Rahbar , Emdadi Manijeh , Khodaei Bahareh , Alishani Mohammad Matin , Boostani Farnaz , Dizaj Solmaz Maleki , Pirmoradi Saeed 
Published: August 2024

Objective
Breast cancer, a global concern predominantly impacting women, poses a significant threat when not identified early. While survival rates for breast cancer patients are typically favorable, the emergence of regional metastases markedly diminishes survival prospects. Detecting metastases and comprehending their molecular underpinnings are crucial for tailoring effective treatments and improving patient survival outcomes.

Methods
Various artificial intelligence methods and techniques were employed in this study to achieve accurate outcomes. Initially, the data was organized and underwent hold-out cross-validation, data cleaning, and normalization. Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. Finally, the selected features were considered, and the SHAP algorithm was utilized to identify the most significant features for enhancing the decoding of dominant molecular mechanisms in lymph node metastases.

Results
In this study, five main steps were followed for the analysis of mRNA expression data: reading, preprocessing, feature selection, classification, and SHAP algorithm. The RF classifier utilized the candidate mRNAs to differentiate between negative and positive categories with an accuracy of 61% and an AUC of 0.6. During the SHAP process, intriguing relationships between the selected mRNAs and positive/negative lymph node status were discovered. The results indicate that GDF5, BAHCC1, LCN2, FGF14-AS2, and IDH2 are among the top five most impactful mRNAs based on their SHAP values.

Conclusion
The prominent identified mRNAs including GDF5, BAHCC1, LCN2, FGF14-AS2, and IDH2, are implicated in lymph node metastasis. This study holds promise in elucidating a thorough insight into key candidate genes that could significantly impact the early detection and tailored therapeutic strategies for lymph node metastasis in patients with breast cancer.
Handheld dynamometry: Validity and reliability of measuring hip joint rate of torque development and peak torque
Authors: McNabb Katherine , Sánchez María B. , Selfe James , Reeves Neil D. , Callaghan Michael 
Published: August 2024

Introduction
Measuring rate of torque development (RTD) and peak torque (PT) for hip muscle performance presents challenges in clinical practice. This study investigated the construct validity of a handheld dynamometer (HHD) versus an isokinetic dynamometer (IKD), and intra-rater repeated reliability for RTD and PT and their relationship in hip joint movements.

Methods
Thirty healthy individuals (mean age = 30 ± 8 years, 13 males) underwent two test sessions in a single day. RTD (0–50, 0–100, 0–150, 0-200ms) and PT normalised to body mass in maximal voluntary isometric contractions were measured using a HHD and an IKD in hip flexion, extension, abduction, adduction, internal and external rotation.

Results
For validity between the devices, RTD0-50 exhibited the largest significant systematic bias in all hip movements (3.41–11.99 Nm·s-1 kg-1) and widest limits-of-agreement, while RTD0-200 had the lowest bias (-1.33–3.99 Nm·s-1 kg-1) and narrowest limits-of-agreement. For PT, agreement between dynamometers was observed for hip flexion (0.08 Nm·kg-1), abduction (-0.09 Nm·kg-1), internal (-0.01 Nm·kg-1), and external rotation (0.05 Nm·kg-1). For reliability, intra-rater intraclass correlation coefficient (ICC2,1) ranged from moderate to good in RTD0-50 and RTD0-100 (0.5–0.88), and good to excellent in RTD0-150 and RTD0-200 (0.87–0.95) in all movements. The HHD displayed excellent intra-rater, relative reliability values (ICC2,1) in all movements (0.85–0.95). Pearson’s correlation revealed good linear correlation between PT and RTD0-150 and RTD0-200 in all movements (r = .7 to .87, p = < .001).

Conclusion
Validity analysis demonstrated significant systematic bias and lack of agreement in RTD measures between the HHD and IKD. However, the HHD displays excellent to moderate intra-rater, relative reliability for RTD and PT measures in hip movements. Clinicians may use the HHD for hip muscle PT assessment but note, late phase RTD measures are more reliable, valid, and relate to PT than early phase RTD. Additionally, the correlation between RTD and PT at various time epochs was examined to better understand the relationship between these measures.
Netflix’ Spain: Critical Perspectives, Jorge González Del Pozo and Xosé Pereira Boán (eds) (2024)
Authors: Meir Christopher 
Published: August 2024

Review of: Netflix’ Spain: Critical Perspectives, Jorge González Del Pozo and Xosé Pereira Boán (eds) (2024)
London: Routledge, 258 pp.,
ISBN 978-1-03255-777-9, h/bk, £135
ISBN 978-1-03255-737-3, p/bk, £35.99
ISBN 978-1-00343-218-0, e-book, £26.99
Culture machines
Authors: Jones Rodney H. 
Published: August 2024

Abstract
This paper discusses the way the concept of culture is discursively constructed by large language models that are trained on massive collections of cultural artefacts and designed to produce probabilistic representations of culture based on this training data. It makes the argument that, no matter how ‘diverse’ their training data is, large language models will always be prone to stereotyping and oversimplification because of the mathematical models that underpin their operations. Efforts to build ‘guardrails’ into systems to reduce their tendency to stereotype can often result in the opposite problem, with issues around culture and ethnicity being ‘invisiblised’. To illustrate this, examples are provided of the stereotypical linguistic styles and cultural attitudes models produce when asked to portray different kinds of ‘persona’. The tendency of large language models to gravitate towards cultural and linguistic generalities is contrasted with trends in intercultural communication towards more fluid, socially situated understandings of interculturality, and implications for the future of cultural representation are discussed.
Plattformnutzung durch Solo-Selbstständige
Authors: Depperschmidt Rina , Matton Heleen , Pongratz Hans , Probst Pia 
Published: August 2024

Zusammenfassung
Plattformarbeit ist für Solo-Selbstständige zu einem wichtigen Erwerbszugang geworden. Dieser Zusammenhang wurde noch wenig untersucht, obwohl der Forschungsstand für beide Erwerbsformen ähnliche Bedingungen ausweist. Mittels einer qualitativen Befragung haben wir die Plattformerfahrungen von 20 Solo-Selbstständigen aus drei Berufsfeldern in vergleichender Perspektive analysiert: Yoga-Lehrer*innen, Sprachlehrer*innen und Creator*innen von Inhalten für die sozialen Medien. Trotz verschiedener Formen der Nutzung von Plattformdiensten sind die Resultate ähnlich: Für kleinere Zusatzeinnahmen ist beträchtlicher Aufwand erforderlich, aber Tools und Informationsangebote der Plattformen machen Arbeitserleichterungen möglich. Die Solo-Selbstständigen erleben viele der aus der Plattformforschung bekannten Abhängigkeiten und verschärften Konkurrenzbedingungen auf Online-Märkten. Nur für wenige Creator*innen führt Plattformarbeit aus einer prekären Selbstständigkeit heraus. Der Beitrag plädiert dafür, die beiden Forschungsfelder stärker zu verbinden und mit institutionellen Absicherungen des solo-selbstständigen Erwerbs auch die Bedingungen von Plattformarbeit zu verbessern.
Designing an ultra-wideband directional antipodal Vivaldi antenna with U-slots for biomedical applications using an optimized attention network
Authors: Borkar Nishant Madhukar , Parlewar Pallavi Keshavrao 
Published: August 2024

Abstract
This research introduces a compact Ultra-Wideband (UWB) antipodal Vivaldi antenna with a U-slot tailored for biomedical applications. Utilizing an elliptical tapered patch variation on a 50*32 mm2 substrate achieves its compact design. Parameter optimization, employing the Multi-Layer Stacked Shallow Attention Neural Network (MLSSANN) with Adaptive Gannet Optimization Algorithm (AGOA), ensures accurate predictions and efficient exploration of the design space. Performance analysis includes metrics like gain, directivity, reflection coefficients, return loss and radiation efficiency. The U-slot variant exhibits higher gain peaking at 24.5 GHz (10 dB) compared to the standard variant peaking near 37 GHz (13.7 dB). The U-slot antenna also shows improved directivity and return loss, with a 13.89 % enhancement in return loss at 3.7 GHz. Moreover, the addition of the slot shifts the lower cut-off frequency from 1,580 MHz to 740 MHz, reducing the antenna size by 41 % while maintaining acceptable radiation characteristics.
Heterogeneous Volatility Information Content for the Realized GARCH Modeling and Forecasting Volatility
Authors: Xu Wen , Aschakulporn Pakorn , Zhang Jin E. 
Published: August 2024

Abstract
As the demand for accuracy in volatility modeling and forecasting increases, the literature tends to incorporate different volatility measures with heterogeneous information content to construct the hybrid volatility model. This study focuses on one of the popular hybrid volatility models: the Realized Generalized Autoregressive Heteroskedasticity (Realized GARCH) and embeds various volatility measures, including the CBOE VIX, VIX1D, Realized Volatility, and Daily Range to examine their heterogeneous impact on the conditional volatility estimation and forecasting. To evaluate the impact of the volatility measures, we first construct a volatility response function. This involves calculating the difference in one-step-ahead conditional volatility forecasts that incorporate information from both return and volatility measures against the forecasts based on return innovations only. Subsequently, the variance share is calculated to evaluate its role in explaining future variations in the Realized GARCH. Our results show that among these four volatility measures, VIX is the most informative volatility. Although VIX1D is overemphasized by the literature, its significance in volatility forecasting remains substantial, confirming that risk-neutral volatility measures are generally more informative than physical measures. Finally, we also find that incorporating multiple risk-neutral volatility measures does not improve forecasting performance compared to using a single measure due to overlapping information.