bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of Frailty on Inpatient Mortality and Resource Utilization for Primary Pulmonary Hypertension
Authors: Rauf Rayaan , Gibson Cheryl A. , Alahmad Mohamad Alhoda Mohamad 
Published: January 2025

Abstract
Background Frailty has been associated with inferior outcomes in patients with primary pulmonary hypertension (PPH). There is a lack of national data to assess if hospital frailty risk score (HFRS) is associated with worse inpatient outcomes in PPH.
Methods Our retrospective study used the Nationwide Readmission Database (NRD). First, we extracted all cases older than 18 years who were discharged with a principal diagnosis of PPH between January and November 2016 to 2019 to allow for a 30-day follow-up. Appropriate survey and domain analyses were applied to obtain national estimates using SAS 9.4.
Results We identified 4,555 cases. HFRS <5 was present in 56% (n = 2,555) of the cohort. Patients with an intermediate-to-high frailty risk score (HFRS ≥5) were older than those with a low frailty risk score (HFRS <5), with a mean age of 61 versus 54 years (p < 0.01), and had slightly fewer women (75 vs. 78%, p = 0.09). Patients with HFRS >5 had a higher prevalence of dementia, depression, diabetes mellitus, malignancy, acute encephalopathy, coagulopathy, heart failure, and chronic (liver and renal) diseases (p < 0.01). Also, they had higher inpatient mortality during index admission (14 vs. 2%, p < 0.001), and all-cause 30-day readmission rates (38 vs. 33%, p = 0.01). Univariate analysis suggests a positive correlation between the degree of frailty and the odds of inpatient mortality (referenced to HFRS <5). The HFRS 5 to 10 group has an odds ratio (OR) of 5 (95% confidence interval [CI]: 3.3–8), the HFRS 10 to 15 group has an OR of 14 (95% CI: 8–23), and the HFRS >15 group has an OR of 20 (95% CI: 9–45). Even after adjusting for age, gender, and significant comorbidities, the single most important factor associated with higher odds of inpatient mortality was HFRS >5 (OR: 5.5 [95% CI: 3.7–8.3], p < 0.001) followed by acute myocardial infarction, acute encephalopathy, heart failure, chronic liver disease, and malnutrition. Length of stay had linear trend with HFRS (mean of 6 days for HFRS <5 vs. 11 days for HFRS 5–10 vs. 19 days for HFRS >10, p < 0.001).
Conclusion Adverse inpatient outcomes correlate with the severity of HFRS in PPH.
Mapping of Endocrinology Training, Certification, and Service Provision in Arab Countries: An Exploratory Survey
Authors: Beshyah Salem A. 
Published: January 2025

Abstract
Background Modern health care and education in Arab countries vary widely. Developing a common understanding of the region's endocrine training, certification, and service models is timely.
Methods We surveyed 63 physicians from 15 Arab countries using an online questionnaire of four domains. They were: (1) informed consent and professional profile; (2) the training, career development, and recognition as an endocrinologist; (3) provision of endocrine services; and (4) the issue of self-proclaimed and recognition of “diabetologists.”
Results Most respondents were senior physicians (82.5%) and adult endocrinologists (53/63). Most respondents (86.7%) confirmed that endocrinology is recognized as a specialty, but only 10.0% stated that it is recognized in major teaching hospitals; 70% of respondents confirmed that a full training program for diabetes and endocrinology exists in their settings; 53.7% stated that postgraduate training in endocrinology requires 2 years with examinations. Half were satisfied, and 25.9% suggested that changes were needed. Regarding endocrine services, 94.8% of respondents reported that the endocrinology is a main service. Diabetes services are reportedly provided mostly by endocrinologists (64.3%). However, nonendocrinologists are involved in diabetes care to a lesser extent. Some specialist services such as lipid clinics, andrology, and reproductive endocrinology are mainly part of endocrinology by 77.2% of respondents and under other specialties by 22.8%. Job opportunities exist primarily in private practice (43.1%) and state hospitals (39.7%). Finally, respondents disagreed with nonendocrinologists' title of “consultant diabetologist” as it is harmful (37.3%) or can be confusing (32.2%) and 22.0% were neutral. Over half (56.7%) stated that academic training courses are welcome to enhance knowledge about diabetes care by primary care doctors but should not be the basis of granting a specialist status.
Conclusions This first look at the mapping of training, certification, and recognition of endocrinologists in Arab countries revealed a wide variation of training systems and care provision. There is a pressing need to address these discrepancies.
Microwave thermal imaging system for debonding detection of radar absorbing materials
Authors: Tu Yihang , Tang Ziqiao , Qiu Yang , Wang Beibei 
Published: January 2025

In this paper, a microwave thermal imaging system (MTIS) has been presented for debonding detection of radar absorbing materials (RAMs). First, an overview of the mechanism underlying microwave heating and the fundamental principle of defect detection within RAMs is presented. Then, a multifunctional MTIS capable of performing both microwave lock-in thermography (MLIT) and long-pulse microwave thermography (LPMT) has been introduced, specifically tailored for the in situ inspection of RAMs. In addition, in this system, the detection area for a single scan is 90 * 90 mm2, with the emission source operating at a frequency of 5.8 GHz and boasting a maximum output power of 20 W. Next, based on MTIS, the above-mentioned two thermography techniques are applied to detect defects in RAMs. In addition, thermal contrast (Tc) and signal-to-noise ratio are introduced for the analysis of imaging results. Finally, the results show that LPMT can be used for preliminary detection of debonding defects in RAMs, while MLIT can be further used for detailed detection of debonding defects in RAMs. In addition, the minimum detection time of this MTIS is 45 s, and the minimum detectable defect aperture is 3 mm.
Progress in understanding the infrared spectrum of the H2O–O2 dimer
Authors: Barclay A. J. , McKellar A. R. W. , Moazzen-Ahmadi N. 
Published: January 2025

Spectra of the weakly bound H2O–O2 dimer are studied in the region of the H2O ν2 band using a tunable quantum cascade laser to probe a pulsed supersonic slit jet expansion. These are the first gas-phase infrared spectra of H2O–O2 and among only a few such results for O2-containing complexes. Almost 100 infrared lines are assigned based on the ground state combination differences from the microwave spectrum of H2O–O2. These lines belong to a main fundamental band, plus four combination bands lying 2 to 5 cm−1 above the fundamental. All correspond to the ortho-H2O (I = 1) nuclear spin species. Interpretation of the observed rotational levels is discussed. The original microwave analysis conflicts with the infrared results but can be corrected by changing the sign of a term or, better still, by using a published theory for weakly bound open shell complexes. The combination bands suggest that analogous ground state bands should be observable in the millimeter wave range. Many infrared transitions remain unassigned, including another extensive band apparently centered at 1603 cm−1, and some of these are probably due to the para-H2O spin species (I = 0). Splittings due to the unpaired O2 electron spin (S = 1), due to large amplitude tunneling motions, and due to a-axis rotational motion all have similar magnitudes for H2O–O2, so the resulting energy levels will be heavily mixed and not amenable to simple modeling. Accurate theoretical predictions of these effects should be possible for obtaining an enhanced understanding of the observed spectra.
Powerful variables for knowledge representation and bracketing
prediction
Authors: Rojas-Garcia Juan 
Published: January 2025

Abstract
The acquisition of knowledge is essential for specialized
translation, and the representation of specialized phraseology in terminological
knowledge bases facilitates this process. The aim of this study is two-fold.
Firstly, it describes how the semantic annotation of the predicate-argument
structure of sentences mentioning named rivers can be addressed from the
perspective of Frame-based Terminology. The results show that this approach,
including the semantic variables of verb lexical domain, semantic role, and
semantic category, provides valuable insights into the knowledge structures
underlying the usage of named rivers in specialized texts. Secondly, this study
explores whether the bracketing of a three-component multiword term can be
predicted from the semantic information encoded in the sentence where the
ternary compound and a named river are used as arguments. The semantic variables
of lexical domain, semantic role, and semantic category allowed us to construct
two machine-learning models capable of accurately predicting ternary-compound
bracketing.
Machine translation post-editing through emotional narratives
Authors: Sánchez Ramos María del Mar 
Published: January 2025

Abstract
Machine translation (MT) and post-editing (PE) have become increasingly common in translation training (Guerberof-Arenas and Moorkens 2019; Sánchez Ramos
2022). However, few studies have explored how trainee translators’ emotional responses to MT and PE impact their
motivation to incorporate these tools in their translation practice. Understanding and managing the emotions of students is
crucial to integrating MT and PE within translator training as a whole, and to fully preparing students for their professional
careers. Building on previous studies applying emotional narrative analysis to translators’ experiences with technology (Koskinen and Ruokonen 2017; Ruokonen and Koskinen
2017), this article explores the emotional responses of a group of 35 Spanish undergraduate translation students to MT
and PE using an emotional narrative methodology. Participants were asked to write an emotional narrative in the form of either a
love letter or a break-up letter addressed to MT. Overall, participants were found to be more positive than negative in their
attitude towards MT and PE. Among the 35 emotional narratives, there were 20 love letters and 15 break-up letters. Thematic
analysis revealed two main themes in the students’ narratives relating to (1) satisfaction with MT output and (2) the efficiency
of MT. These exploratory findings reinforce Yang and Wang’s (2019) call for more
research into what factors contribute to students’ intention to use MT and the consequent effects of using MT. They can also
inform pedagogy so that translator trainers better understand the factors that motivate students to incorporate MT in their
translation practice.
Effects of pulse rise rate and pulse width on the dynamics of secondary streamers and radical production in atmospheric-pressure air
Authors: Zheng Xinlei , Zheng Haotian , Sun Zihan , Zhao Zheng , Li Jiangtao 
Published: January 2025

Abstract
The role of the secondary streamer in radical production has been extensively studied, while most of studies analyzed the secondary streamer by assuming a constant electric field in the secondary streamer, thereby ignoring the dynamic nature of the secondary streamer. In this study, the dynamics of the secondary streamer and the effects of pulse rise rate and pulse width are investigated using simulations. The temporal evolution of the secondary streamer under pulsed voltage is analyzed using a novel model. The results shows that the electric field in the secondary streamer first decreases linearly with the length of the secondary streamer, and then changes with the pulsed voltage after the cessation of the secondary streamer. The decrease of the electric field in the secondary streamer is the dominant factor responsible for the cessation of the secondary streamer. As a result, radicals are predominantly produced prior to the cessation of the secondary streamer. By understanding the dynamics of the secondary streamer, it becomes possible to control the electric field and length of the secondary streamer by adjusting the pulse rise rate and pulse width, respectively, to enhance the energy efficiency of radical production. The increase in the length of the secondary streamer is always advantageous for improving energy efficiency, as it leads to greater energy deposition within the secondary streamer. For N(4S), the optimal electric field is approximately 600 Td, which cannot be achieved in the secondary streamer. In contrast, for O(3P), the optimal electric field is around 180 Td, which can be attained by regulating the voltage waveform.
Underdetermined blind source separation with adaptive chirp mode decomposition for compound rolling bearing fault signals
Authors: Liao Xiangyu , Chen Qian , Xiang Jiawei 
Published: January 2025

Abstract
The challenge of underdetermined blind source separation (UBSS) is on the need to separate multiple fault signals from a single-channel signal. Conventional separation algorithms are restricted by the lack of sufficient information to extract multiple source signal characteristics. To tackle the challenge, this paper introduces a novel method that combines sparse denoising-aided adaptive chirp mode decomposition (ACMD) with fast independent component analysis (FastICA). The underdetermined problem is transformed into a well-determined one by using decomposition techniques. Firstly, enhanced sparsity of GMC is used to denoise the collected signal and further enhance fault features. Next, the denoised signal is decomposed into multiple intrinsic mode functions (IMFs) using ACMD. Subsequently, the optimal IMFs are selected and then constructed a new observation signal, which is then used as the input for FastICA. At the same time, singular value decomposition is performed on each decomposed IMF to obtain the corresponding singular values, which are determined the number of signal sources and the separation layers of the FastICA method by the maximum ratio between adjacent singular values. Ultimately, the constructed observation signal is separated. This method is applied to single-channel UBSS of compound faults in rolling bearings. Numerical simulations and experimental studies demonstrate the method’s effectiveness.
Cosmic topology. Part Ic. Limits on lens spaces from circle searches
Authors: Saha Samanta , Copi Craig J. , Starkman Glenn D. , Anselmi Stefano , Duque Javier Carrón , Barandiaran Mikel Martin , Akrami Yashar , Cornet-Gomez Fernando , Jaffe Andrew H. , Kosowsky Arthur , Mihaylov Deyan P. , Pereira Thiago S. , Samandar Amirhossein , Tamosiunas Andrius ,   The COMPACT collaboration
Published: January 2025

Abstract
Cosmic microwave background (CMB) temperature and polarization observations indicate that in the best-fit Λ Cold Dark Matter model of the Universe, the local geometry is consistent with at most a small amount of positive or negative curvature, i.e., |Ω
K
| ≪ 1.
However, whether the geometry is flat (E
3), positively curved (S
3) or negatively curved (H
3), there are many possible topologies.
Among the topologies of S
3 geometry, the lens spaces L(p,q), where p and q (p > 1 and 0 < q < p) are positive integers, are quotients of the covering space of S
3 (the three-sphere) by ℤ
p
, the cyclic group of order p.
We use the absence of any pair of circles on the CMB sky with matching patterns of temperature fluctuations to establish constraints on p and q as a function of the curvature scale that are considerably stronger than those previously asserted for most values of p and q.
The smaller the value of |Ω
K
|, i.e., the larger the curvature radius, the larger the maximum allowed value of p.
For example, if |Ω
K
| ≃ 0.05 then p ≤ 9, while if |Ω
K
| ≃ 0.02, p can be as high as 24.
Future work will extend these constraints to a wider set of S
3 topologies.
Geometry based and simulation supported porosity prediction in ductile iron casting
Authors: Sata Amit , Maheta Nikunj , Dave Anjali , Khandelwal Himanshu 
Published: January 2025

Abstract
Shrinkage porosity is one of the significant challenge in metal casting process that influence productivity and energy efficiency particularly with castings that are not produced as per the requirement of Original Equipment Manufacturers (OEMs). To address this issue, proactive measures and predictive techniques are essential. Among these, the criterion function stands out as an important empirical model widely explored in the literature. It intricately connects solidification process to the development of shrinkage porosity by considering the key variables such as molten metal velocity during solidification, cooling rate and thermal gradient to offer predictive insights into the position and existence of porosity. It is necessary to establish a criterion function that takes into account the impact of geometric variation on the degree of shrinkage porosity. In this paper, a geometry-based quantitative prediction model for ductile iron castings was developed using a standard shape of a casting with three T-joints. By correlating actual experimental data with solidification simulation results, meaningful insights were obtained and extrapolated. The resulting quantitative prediction model that incorporates the effects of geometric variation has been validated and provides better prediction of shrinkage porosity.
Deep learning-based real-time detection and classification of tomato ripeness stages using YOLOv8 on raspberry Pi
Authors: Nahiduzzaman Md , Sarmun Rusab , Khandakar Amith , Faisal Md Ahsan Atick , Islam Munshi Sajidul , Alam Mohammad Kaoser , Rahman Tawsifur , Al-Emadi Nasser , Murugappan M , Chowdhury Muhammad E H 
Published: January 2025

Abstract
The automated detection of tomato ripeness is critical in crop management and harvesting. In most earlier works, tomato image ripeness detection has been based upon a limited set of images and binary classification (ripe and unripe). This study uses the cutting-edge YOLOv8 object detection algorithm and a comprehensive dataset to propose an accurate real-time system for detecting and classifying tomato ripeness (multi-class). Based on two open-source datasets (Kaggle and Internet-sourced), we developed and tested the proposed system. In this method, a comprehensive tomato image dataset is curated, YOLOv8 models are built, seamlessly integrated into an embedded system (Raspberry Pi4), then evaluated and validated. The model shows exceptional performance in detecting three distinct classes of ripeness: unripe, partially ripe, and ripe. It surpasses existing state-of-the-art models in both accuracy and efficiency. Based on the Kaggle dataset, our model achieves an average precision at 50 of 0.808, with F1-scores of 0.80, 0.65, and 0.796 for unripe, partially ripe, and ripe classes, respectively. It achieves mAP at 50 of 0.725 and F1-scores of 0.747 (unripe), 0.652 (partially ripe), and 0.72 (ripe) for the corresponding classes of the Internet-sourced Dataset, exceeding current state-of-the-art models. Finally, the proposed tomato ripeness detection algorithm is implemented on the Raspberry Pi 4 system and exhibits notable performance. With the integration of YOLOv8 into an embedded system (Respbeery Pi4), it can be used to improve efficiency and reduce labor costs in tomato-picking robots, helping to revolutionize agricultural practices.
A comprehensive SCAPS-1D simulation study on the photovoltaic properties and efficiency enhancement of CH3NH3PbCl3 perovskite solar cells
Authors: Kabir Md Raihan , Ishraq Md Hasin , Tarekuzzaman Md , Nahid Nazmul Islam , Modak Jibon Krishna , Ahmad Sohail , Arfi Asif Mohammed , Rasheduzzaman Md , Hasan Md Zahid 
Published: January 2025

Abstract
Recent progress in lead (Pb) halide perovskites has inspired much research into economical solar cells, focusing on critical issues of stability and toxicity. This study investigates the performance of perovskite solar cells (PSCs) by simulating the impact of a methylammonium lead chloride (CH3NH3PbCl3) layer as the absorber material using the SCAPS-1D simulator. The first comprehensive study of this material examines the role and configuration of the Electron Transport Layer (ETL) and Hole Transport Layer (HTL), as well as the absorber layer, on solar cell performance. The ETLs used in the device optimization are ZnO, SnO2, IGZO, and CdS; the HTL is CuO; and the front and back contacts are Au and Ni, respectively. The study highlights CuO as the optimal HTL for CH3NH3PbCl3, delivering power conversion efficiencies (PCEs) of 16.10%, 16.06%, 16.05%, and 14.41% with ZnO, SnO2, IGZO, and CdS as ETLs, respectively. The performance of these device architectures is significantly influenced by factors such as defect density, absorber layer thickness, ETL thickness, and the combination of different ETLs and CuO HTLs. Furthermore, this study elucidates the impact of absorber and HTL thickness on key photovoltaic parameters, such as VOC, JSC, FF, and PCE. Also, we have discussed the VBO, and CBO for different ETLs. Additionally, we examine the effects of series and shunt resistance, operating temperature, quantum efficiency (QE), capacitance–voltage characteristics, generation and recombination rates, and current density–voltage (J-V), analysis of absorption data, and impedance analysis behavior on achieving the highest efficiency of the device. This comprehensive study provides critical insights into designing cost-effective, high-performance PSCs, and advancing the development of next-generation photovoltaic technologies.
Multilingual AI system for detecting offensive content across text, audio, and visual media
Authors: Koreddi Venkatesh , Manisha Nalluri , Kaif Shaik Mohammad , Kumar Yeligeti Tejaswa Sai 
Published: January 2025

Abstract
This paper aims to develop an AI system with advanced capabilities to detect offensive language across diverse platforms-covering text, audio (both live and recorded speech), and images (such as memes)—in multiple languages. Using technologies such as natural language processing (NLP), speech recognition (SR), and optical character recognition (OCR) to identify text within images, the system can already flag potentially harmful or inappropriate content. Integration with Google Translator ensures automatic detection and translation of input languages, enabling global applicability and enhanced reliability. For text analysis, the system utilizes BERT (Bidirectional Encoder Representations from Transformers), a large, pretrained model known for its strong contextual and semantic comprehension of human language. As the digital landscape rapidly evolves, precise identification of offensive content is becoming increasingly essential. Through this project, we are building robust, fair and impactful technology to foster safer online environments for all users, addressing this significant challenge head on.
Pluralism in the Justification of Punishment
Authors: Zaibert Leo 
Published: January 2025

Abstract
Contemporary non-retributive justifications of punishment inherit the excesses of the positivist ethos of Beccaria and Bentham. All that these justifications seek to do is to reduce suffering: they are, in Leibniz’s sense, medicinal. The consideration of Roberts’ seemingly innocuous disanalogy between the criminal justice system and the healthcare system foregrounds a welcome alternative: Roberts’ approach to criminal justice is profoundly non-medicinal and indeed profoundly pluralistic. Like any sensible person, Roberts also seeks to diminish suffering in the world—but not by ignoring the complexity of punishment. One of the central challenges of retributive justice (the justice that is of concern for the criminal justice system) is that we achieve the good of justice by means of making people suffer. To reduce suffering simply by ignoring the value of justice is a naïve and uninspiring—yet widespread—strategy. In this regard (as in many others), Roberts’ vast oeuvre stands tall in tackling so many aspects—including so many practical aspects—of the criminal justice system without ever losing sight that justice matters.