bluuebunny/crossref_metadata_2025_split huggingface dataset:
Measurement of Solar Differential Rotation by Absolutely Calibrated Iodine-Cell Spectroscopy
Authors: Takeda Yoichi 
Published: March 2024

Abstract

The iodine-cell technique, which is known to be efficient in precisely establishing Doppler velocity shifts, was once applied by the author to measuring the solar differential rotation based on full-disk spectroscopic observations (Takeda and Ueno, 2011). However, the data reduction procedure (in simple analogy with the stellar case) adopted therein was not necessarily adequate, because specific characteristic involved with the disk-resolved Sun (i.e., center–limb variation of line strengths) was not properly taken into consideration. Therefore, this problem is revisited based on the same data but with an application of theoretical spectrum fitting, which can yield absolute heliocentric radial velocities (vobs) in a consistent manner as shown in the study of solar gravitational redshift (Takeda and Ueno, 2012). Likewise, instead of converting vobs into ω (angular velocity) at each disk point, which suffers considerable errors especially near to the meridian, ω was derived this time by applying the least squares analysis to a data set comprising vobs values at many points. This new analysis resulted in ω (deg day−1) = 13.92(±0.03) −1.69(±0.34) sin ψ2 −2.37(±0.62) sin4 ψ (ψ: heliographic latitude) along with the gravitational redshift of 675 m s−1, which are favorably compared with previous publications. In addition, how the distribution of observing points on the disk affects the result is also examined, which reveals that rotation parameters may suffer appreciable errors depending on cases.
Specification Overfitting in Artificial Intelligence
Authors: Roth Benjamin , de Araujo Pedro Henrique Luz , Xia Yuxi , Kaltenbrunner Saskia , Korab Christoph 
Published: March 2024

Abstract

Machine learning (ML) and artificial intelligence (AI) approaches are often criticized for their inherent bias and for their lack of control, accountability, and transparency. Consequently, regulatory bodies struggle with containing this technology's potential negative side effects. High-level requirements such as fairness and robustness need to be formalized into concrete specification metrics, imperfect proxies that capture isolated aspects of the underlying requirements. Given possible trade-offs between different metrics and their vulnerability to over-optimization, integrating specification metrics in system development processes is not trivial. This paper defines specification overfitting, a scenario where systems focus excessively on specified metrics to the detriment of high-level requirements and task performance. We present an extensive literature survey to categorize how researchers propose, measure, and optimize specification metrics in several AI fields (e.g., natural language processing, computer vision, reinforcement learning). Using a keyword-based search on papers from major AI conferences and journals between 2018 and mid-2023, we identify and analyze 74 papers that propose or optimize specification metrics. We find that although most papers implicitly address specification overfitting (e.g., by reporting more than one specification metric), they rarely discuss which role specification metrics should play in system development or explicitly define the scope and assumptions behind metric formulations.
Experimental study of dynamic wetting behavior through curved microchannels with automated image analysis
Authors: Zhang Huijie , Lippert Anja , Leonhardt Ronny , Tolle Tobias , Nagel Luise , Fricke Mathis , Maric Tomislav 
Published: March 2024

Abstract

Preventing fluid penetration poses a challenging reliability concern in the context of power electronics, which is usually caused by unforeseen microfractures along the sealing joints. A better and more reliable product design heavily depends on the understanding of the dynamic wetting processes happening inside these complex microfractures, i.e. microchannels. A novel automated image processing procedure is proposed in this work for analyzing the moving interface and the dynamic contact angle in microchannels. In particular, the developed method is advantageous for experiments involving non-transparent samples, where extracting the fluid interface geometry poses a significant challenge. The developed method is validated with theoretical values and manual measurements and exhibits high accuracy. The implementation is made publicly available.The developed method is validated and applied to experimental investigations of forced wetting with two working fluids (water and 50 wt\% Glycerin/water mixture) in four distinct microchannels characterized by different dimensions and curvature. The comparison between the experimental results and molecular kinetic theory (MKT) reveals that the dynamic wetting behavior can be described well by MKT, even in highly curved microchannels. The dynamic wetting behavior shows a strong dependency on the channel geometry and curvature.
Breaking New Ground in Online Apparel Shopping: AI-Driven 3D Modeling from 2D Images for Precise Sizing and Fit
Authors: Nasarullah Muhammad Umair , Abbas Ghulam , Ramzan Abdullah , Perwaiz Nazia , Zahid Zunera , Bhatti Iram Tariq 
Published: March 2024

Abstract
This paper outlines a pioneering research endeavor focused on addressing a prevalent challenge in online clothing shopping: the quest for accurate size and fit. Our innovative approach delves into leveraging artificial intelligence-driven 3D mod-eling techniques to extract precise anthropometric measurements of the human body, utilizing straightforward hardware coupled with sophisticated image processing and computer vision methodologies. The primary objective is to craft a scalable, user-friendly application aimed at streamlining the online clothes shopping experience, eliminating uncertainties for customers and enhancing efficiency.
Our proposed methodology amalgamates two distinct anthropometric measurement techniques. Firstly, we employ feature point extraction utilizing the Medi-apipe pose estimation neural network. Additionally, a bespoke tape measurement algorithm harnesses robust image processing tools and libraries. Furthermore, ongoing research delves into employing NERF (Neural Radiance Field) and deep learning techniques to refine the accuracy of our 3D models, specifically targeting intricate measurements such as the Neck and Waist.
While extant solutions exist for deriving anthropometric measurements from photographic images, our project pioneers the use of 3D models for precise 1 measurements, potentially revolutionizing the online shopping landscape. This ongoing research endeavors to continually explore novel methodologies, striving to enhance the accuracy and usability of our application.
Chronic kidney disease and osteoporosis: a two-sample Mendelian randomization study
Authors: An Jiaqi , Shi Jing-xuan , Liu Xin-ze , Jiao Yuan-yuan , Tian Jing-wei , Yang Yue , Lu Hai-tao , Zhuo Li 
Published: March 2024

Abstract

Purpose:The study aims to assess the causal relationship between chronic kidney disease and osteoporosis through two-sample Mendelian randomization.Methods:The Chronic Kidney Disease Genetics Consortium identified specific single nucleotide polymorphisms (SNPs) linked to eGFR and UACR, used as instrumental variables in a two-sample Mendelian Randomization (MR) analysis. This analysis, primarily using the inverse variance-weighted (IVW) method, aimed to explore the causal connections between CKD and bone health risks, specifically fractures, osteoporosis, and BMD. Data for these bone health risks were sourced from a GWAS database. Validation of results employed MR-Egger regression, weighted median estimation (WME), and weighted mode. The MR-PRESSO and MR-Egger intercept tests checked for horizontal pleiotropy in SNPs, while the Q-test and leave-one-out analysis assessed result heterogeneity.Results:IVW results (OR=1.022, 95% CI=1.009-1.035, P<0.001) and MR-Egger regression results (OR=1.023, 95% CI=1.002-1.045, P=0.034) both indicate a causal relationship between CKD and osteoporosis. IVW suggests a suggestive impact of UACR on ankle bone density (IVW: β=-0.158, 95% CI: -0.312 to 0.005, P=0.043; WME: β=-0.12, 95% CI: -0.327 to 0.017, P=0.037), but the results are not robust. No causal relationship was observed for fractures, whole-body bone density, forearm bone density, vertebral bone density, and hip neck bone density.Conclusion:Our MR analysis indicated that lower eGFR is associated with osteoporosis (OP). Although CKD potentially affects skeletal health and may causally link to OP, current evidence is insufficient to confirm its genetic impact on fractures and bone density. Additional analysis with more cases is needed.
The Role of SOX 2 Gene in Cervical Cancer: Focus on Iron Death and Construct a Predictive Model
Authors: Liu Shenping , Wei Zhi , Ding Huiqing 
Published: March 2024

Abstract

Background
The intricate interplay between stemness markers and cell death pathways significantly influences the pathophysiology of cervical cancer. SOX2, a pivotal regulator of stem cell pluripotency, has recently been implicated in the modulation of ferroptosis, a specialized form of iron-dependent cell death, in cancer dynamics. This study delineates the role of SOX2 in the ferroptotic landscape of cervical carcinoma.
Objective
To delineate the association between SOX2 expression and ferroptosis in cervical cancer and develop a robust, SOX2-centric predictive model for patient prognosis, enhancing personalized therapeutic approaches.
Methods
A multi-dimensional approach integrating advanced bioinformatics, comprehensive molecular profiling, and state-of-the-art machine learning algorithms was employed to assess SOX2 expression patterns and their correlation with ferroptotic markers in cervical cancer tissues. The prognostic model was meticulously crafted, incorporating SOX2 expression levels and ferroptosis indicators.
Results
The investigation unveiled a profound and intricate correlation between SOX2 expression and ferroptotic processes in cervical cancer, substantiated by robust molecular evidence. The developed predictive model, underpinned by SOX2 expression, exhibited superior predictive accuracy for patient prognosis, potentially guiding therapeutic decision-making.
Conclusion
This study underscores the critical role of SOX2 in orchestrating the ferroptotic pathway in cervical cancer, presenting a novel prognostic framework. The SOX2-centric predictive model emerges as a significant advancement in prognostic evaluation, offering a gateway to precision oncology in the realm of gynecologic oncology.
Broiler mesenchymal stem cells and curcumin: Evaluation of curcumin differentiation potential on broiler adipose-derived mesenchymal stem cells
Authors: Golroodbari Pooya Jahandideh , Ziabari Mina Salkhordeh , Goushki Mehdi Amiri , Bos-hagh Somayeh , Mahdavi Fatemeh Sadat , Sharifi Seyed Davood , Khodaei-Motlagh Mahdi , Rafeie Farjad , Rahimi Amin , Seyedjafari Ehsan , Mohammadi-Sangcheshmeh Abdollah 
Published: March 2024

Abstract
Excessive body fat deposition is poultry production challenge. Curcumin impact on inhibiting fatty acid biosynthesis and increasing glycogen synthesis, were evaluated in different researches. So, the current study aims to identify the effect of curcumin on broiler stem cells differentiation. Isolated cells were cultured for 4–7 days and the growth pattern was evaluated. To investigate curcumin impact, the cells in passage 2 were treated and compared with basal differentiation medium and curcumin in the concentration of 1, 5, 10, 15, and 20 µM in 11 days; furthermore, the MTT assay was done to evaluate curcumin toxify. The osteogenic differentiation was assayed by calculating calcium deposition, alkaline phosphatase activity, and the expression of osteogenic markers (RUNIX 2, COL-1, ALP) and the Alizarin Red S staining method. And for adipogenic differentiation, expression of related gene markers (PPARγ, FABP4) and Oil Red O staining was used. The MTT result indicated that curcumin has no toxic effect (p < 0.05). Furthermore, curcumin showed a higher (p < 0.05) alkaline phosphatase activity and more (p < 0.05) calcium content and the expression of the corresponding gene increased (p < 0.05), while prevents adipogenic differentiation (p < 0.05). This information demonstrates that curcumin causes osteogenic differentiation and prevent stem cells from differentiating to adipose cells.
Translation, cross-cultural adaptation and validation of the General Movement checklist
Authors: Salazar-Díaz Daniela E , Viñals-Labañino Carlos P. , Balderas-Campos Marcela , Alvarado-Solorio Elsa , Arenas-Sordo María L. 
Published: March 2024

Abstract

Background.
The General Movement checklist, recently developed by Aizawa et al. is an alternative, accessible, and affordable tool for usage by health care professionals who are not certified or trained in Prechtl's General Movement Assessment.
Aim
To validate of the Spanish version of the General Movement checklist in preterm and full-term Mexican children and to evaluate its reliability, content, criterion and predictive validity.
Methods
Observational, cross-sectional, descriptive study. Videos of preterm and term infants at high neurological risk were included. The inter- and intraobserver reliability of the General Movement checklist in its original version was analysed. Translation and cross-cultural adaptation to Spanish were performed, following international guidelines. Content, criterion and predictive validity were determined using the General Movement Optimality Score-Revised (GMOS-R) and the clinical diagnosis at 2 years corrected age. Receiver Operating Characteristic (ROC) curves were generated to identify the cut-off points on the General Movement checklist.
Results
The reliability of the instrument was very good. According to the experts, the content validity of the Spanish versión of the instrument was good. A total of 105 videos were evaluated using the Spanish version of the instrument. High sensitivity and specificity were obtained when comparing the results with the GMOS-R and clinical diagnosis and a cut-off point of 10 was determined.
Conclusions
The Spanish version of the General Movement checklist is a reliable and valid instrument for its use in the Mexican population and it could also be used in some other Spanish-speaking populations,
The Impact of Technological Innovation on the Spatial Agglomeration Effect of China's Pharmaceutical Manufacturing Industry: an Empirical study based on a semi Parametric Spatial Lag Model
Authors: Zhang Xinduo , Wang Jiaxin , Fu Shuyong 
Published: March 2024

Abstract
The purpose is to explore the relationship between technological innovation and industrial development in China's pharmaceutical manufacturing industry. The method is to use the panel data of 29 provinces in China from 2009 to 2021 based on the semi-parametric spatial lag model. The results show that the industrial development of the pharmaceutical manufacturing industry has a significant negative spatial spillover effect, and the coefficient is -0.104 in the semi-parametric spatial lag model. The technological innovation of the pharmaceutical manufacturing industry has a nonlinear influence on its industrial development, and the marginal effect of the two shows a inhibitor-promotion-inhibitor-promotion-inhibition fluctuation relationship. The conclusion is that we should promote the communication and cooperation between the regions with relatively weak technological innovation and the regions with strong technological innovation. Promote domestic leading pharmaceutical enterprises to increase investment in research and development of innovative drugs in order to participate in international competition.
Promotion of trust through the advertising message during the Covid-19 pandemic.
Authors: Antonicelli Margaret , D'Uggento Angela Maria , Marin Claudia 
Published: March 2024

Abstract
Researchers have increasingly focused on social media as a valuable source of data production to capture and analyze people's opinions on various topics. When extreme events occur, netizens can quickly spread opinions online, generating an impact that can have both positive and negative implications. Twitter is one such platform that allows people to learn about events and facts happening in the world, including epidemics, and express their opinions. Therefore, governments, companies and other organizations to learn about public sentiment and respond with institutional messages or emotional support can use social media. During the Covid-19 pandemic, many companies have used television commercials to instill trust and hope in individuals, especially in families, promoting solidarity and brotherhood, while keeping the brand in the background. This article aims to define an evaluation metric to measure the effectiveness of the advertising change of large brands using a corpus of 20,982 tweets, using indicators created following results obtained from sentiment analysis. Our findings suggest that internet users experienced a sense of belonging and appreciation during lockdown, as well as a positive attitude towards television advertising that was previously perceived as disruptive.
Cardiogenic Shock in Puerperal Patient: Uncommon Immunological Complication a Case Report and Literature Review
Authors: Marenco Mario López , Mercado David , Montoya-Rodríguez Arlin 
Published: March 2024

Abstract

A 34-year-old woman with a history of chronic hypertension and two previous cesarean sections presented with symptoms of preeclampsia and fetal growth restriction in her 35th week of pregnancy. The condition progressed to preterm labor, resulting in an emergency cesarean section. Two weeks postpartum, she developed fever, dyspnea, and joint pain. Investigation revealed cardiomegaly, pulmonary edema, and severe ventricular dysfunction. Laboratory tests confirmed autoimmune markers consistent with systemic lupus erythematosus (SLE) and antiphospholipid syndrome (APS). She was diagnosed with acute myocarditis related to SLE/APS and managed with inotropic support, diuretics and immunosuppression. Left ventricular function improved, and she was discharged with ongoing rheumatologic follow-up. This case highlights the complex interplay between peripartum complications, autoimmune diseases, and cardiac involvement, emphasizing the importance of early diagnosis and multidisciplinary management.
NeuDen: A Framework for the Integration of Neuromorphic Evolving Spiking Neural Networks with Dynamic Evolving Neuro-Fuzzy Systems for Predictive and Explainable Modelling of Streaming Data
Authors: AbouHassan Iman , Kasabov Nikola 
Published: March 2024

Abstract

This paper introduces a novel framework, called here 'NeuDen' for the integration of neuromorphic evolving spiking neural networks (eSNN), that learn efficiently multiple time series in their temporal association and interaction, with dynamic evolving neuro-fuzzy systems (deNFS), that learn incrementally extracted from the eSNN feature vectors, to predict future time-series values and to produce interpretable fuzzy rules. The new framework aims to make the best out of the dominant features of the two types of models. First, spike-time-dependent plasticity (STDP) learning is used in SNN to learn temporal interaction between multiple time series, connected to a dynamic eSNN (deSNN) as a regressor/classifier. Then, feature-vectors are extracted from the trained deSNN for further learning, fuzzy inference and rule extraction in a deNFS, here exemplified by DENFIS, resulting in an accurate prediction results and explainable dynamic fuzzy rules. The NeuDen, framework and model, overcomes both the explainability problems of eSNN and the limitations of deNFS to model multiple streaming time series in their temporal interaction. NeuDen surpasses both deSNN and DENFIS by providing multiple regression models and achieving higher accuracy. NeuDen is demonstrated on bench mark data and on financial and economic time series, achieving from 3 to 100 times smaller RMSE when compared with other evolving systems. The proposed framework opens a new direction for the development of more efficient evolving systems by integrating eSNN with other methods, such as other neuro-fuzzy systems, deep neural networks and quantum classifiers for specific applications.
An Overview of Contemporary and Future Therapeutic Strategies for
Scalp Psoriasis
Authors: Soni Bindu , Shivgotra Riya , Trehan Karan , Chhina Aashveen , Saini Muskaan , Jain Subheet Kumar , Thakur Shubham 
Published: March 2024

Abstract:
Scalp psoriasis is a common manifestation of psoriasis that significantly impacts a patient's
quality of life. About 80% of cases of psoriasis involve the scalp, making it the most frequently
affected area of the body. The treatment of scalp psoriasis is particularly crucial because
of its hard-to-treat nature and substantial adverse impacts on overall well-being. Along with the
physical symptoms of discomfort and itching, psoriasis, especially when it affects the scalp, can
cause severe psychological damage. Treating scalp psoriasis can be challenging due to its location
and associated symptoms, such as scaling and pruritus, which is why various drugs have become
widely used for refractory cases. Topical treatments like corticosteroids and vitamin D analogs manage
scalp psoriasis by reducing inflammation and regulating skin cell growth. Tar-based shampoos,
salicylic acid solutions, and moisturizers control scaling. Phototherapy with UVB light reduces
inflammation. Severe cases may require systemic medications such as oral retinoids and immunosuppressants.
While various therapies are accessible for scalp psoriasis, concerns arise due
to their limited advantages and the absence of controlled studies assessing their effectiveness. Considering
these challenges, there is a clear demand for innovative approaches to address this condition
effectively. Recent advancements in topical therapies, phototherapy, systemic agents, and
complementary therapies have shown promising results in managing scalp psoriasis. Also, the advent
of biologics, specifically anti-IL-17 and anti-IL-23 drugs for scalp psoriasis, has seen significant
improvements. The review highlights the lack of well-tolerated and effective treatments for
scalp psoriasis and underscores the importance of further research in this area. The objective of
this review is to clarify the different treatment options currently available or being investigated in
clinical trials for managing scalp psoriasis.
Synthetic Strategies of Thiazolidine-2,4-dione Derivatives for the
Development of New Anti-diabetic Agents: Compressive Review
Authors: Ray Pushkar Kumar , Shabana Km , Salahuddin  , Kumar Rajnish 
Published: March 2024

Background:
Thiazolidine-2,4-dione (2,4-TZD) is a flexible pharmacophore and a privileged platform and contains a five-membered ring with a 2-oxygen atom with double bond 2,4- position and one nitrogen atom as well as sulphur containing in the heterocyclic compound. A famous electron-rich nitrogen transporter combines invigorating electronic properties with the prospective for elemental applications. Thiazolidine-2,4-dione analogues have been synthesized using a variety of methods, all of which have shown to have a strong biological effect.

Objective:
The study of the biological activity of Thiazolidine-2,4-dione derivatives has been a fascinating field of pharmaceutical chemistry and has many purposes. This derivative described in the literature between 1995 to 2023 was the focus of this study. Thiazolidine-2,4-diones have been discussed in terms of their introduction, general method, synthetic scheme and antidiabetic significance in the current review.

Conclusion:
Thiazolidine-2,4-diones are well-known heterocyclic compounds. The synthesis of Thiazolidine-2,4-diones has been described using a variety of methods. Antidiabetic activity has been discovered in several Thiazolidine-2,4-dione derivatives, which enhance further research. The use of Thiazolidine-2,4-diones to treat antidiabetics has piqued researchers' interest in learn-ing more about Thiazolidine-2,4-diones.