bluuebunny/crossref_metadata_2025_split huggingface dataset:
Marchitez por Fusarium oxysporum Schlthl en masaguaro (Pseudosamanea guachapele) (Kunth).
Authors: Castellanos González Leonides , Monroy Gonzalez Hermes H. , Rivera Ochoa Xiomara G. 
Published: July 2024

Introducción— El masaguaro (Pseudomanea Guachapele) fue utilizado en la reforestación por la ”Fundación Orinoquia Biodiversa” en Arauca y presentó un marchitamiento desconocido.
Objetivo— Caracterizar la enfermedad y su agente causal, y evaluar el posible control químico y biológico de la enfermedad.
Metodología— La investigación se realizó en el barrio Campo Alegre Arauquita (Arauca, Colombia). Las muestras se analizaron en el laboratorio de microbiología de la Universidad de Pamplona. Se caracterizó la enfermedad y su agente causal, se determinó la incidencia y severidad de la enfermedad y se estimaron las pérdidas monetarias considerando las plantas muertas. Se realizó un experimento de control de marchitez utilizando benomyl y Bacillus subtilis, comparándolos con un control sin tratamiento.
Resultados— Fusarium oxysporum fue identificado como agente causal de la enfermedad. El marchitamiento alcanzó entre el 13% y el 54% de incidencia. Las pérdidas económicas se estimaron en más de 19 millones de pesos / ha.
Conclusión— Se verificó la acción preventiva y erradicativa de benomyl y solo acción preventiva de B. subtilis.
Esbeltez en Sistemas Marco Muro: Factores correctivos para el Valle de México
Authors: Berruecos Licona Sergio Omar , Esteva Maraboto Luis , García Benitez Silvia Raquel 
Published: July 2024

Introducción— Las metodologías y procedimientos utilizados en el diseño de edificaciones que muestra el Reglamento de Construcciones de la Ciudad de México 2017 están basadas en técnicas de confiabilidad y desempeño, sin embargo, los factores que se aplican en esta norma para sistemas irregulares tienen fundamento en la práctica ingenieril.
Objetivo— El objetivo de esta investigación es la obtención de factores correctivos aplicables a la normatividad de mexicana para el diseño de estructuras de concreto con características de esbeltez y con sistema marco-muro.
Metodología— Se realizó el análisis, diseño y comparativa de dos familias de edificios de concreto con sistema dual, la primera familia se caracteriza por cumplir con los requisitos de regularidad delimitadas en la normativa, la segunda familia irrumpe con el requisito de esbeltez, ambas familias están formadas por edificios de 11, 15 y 20 niveles. De cada edificio se creo una muestra con un mínimo de 50 edificios mediante el método de Montecarlo variando sus propiedades mecánicas, geométricas, cargas vivas, cargas muertas y acciones sísmicas representativas. Las muestras fueron evaluadas mediante un análisis de confiabilidad y posteriormente comparadas.
Resultados— Se dan recomendaciones para la obtención de factores basados en confiabilidad y desempeño asociadas a una aceleración específica del terreno y diferentes grados de esbeltez.
Conclusiones— El reglamento de Construcciones de la Ciudad de México contempla únicamente el factor de irregularidad por esbeltez cuando la relación altura/base es mayor a 4 y además se cuente con otra irregularidad en la edificación. Este estudio muestra que los edificios con relaciones de esbeltez mayores que 4 deben ser consideradas como irregulares y debe aplicarse un factor correctivo de acuerdo con su grado de esbeltez, esto a su vez sin haber infringido alguna otra irregularidad.
Unveiling the relationship: Sacroiliac Joint Dysfunction as an Overlooked Factor in Lumbar Back Pain
Authors: Valerio Pascua Jose E. , Santiago Rea Noe , Fernandez Gomez Maria P. , Maraone Garzaro Andrea V. , Alvarez-Pinzon Andres M. 
Published: July 2024

Introduction: The Sacroiliac joint (SIJ) is a crucial connection found between the sacrum and ilium. It plays a vital role in transferring forces during physical activity, such as running. Its biomechanical function is crucial for ensuring stability, as it is supported by ligaments and pelvic floor muscles that work together to ensure this for individuals. However, SIJ dysfunction can be linked to lower back pain, which is a condition that affects around 70-85% of Western society. Causes: SIJ dysfunction originates from various factors, such as abnormal motion or malalignment. These conditions can arise from multiple causes: arthritis, trauma, or nontypical gait patterns. Diagnosis: Physical examinations are included in the diagnosis of SIJ dysfunction. They are called FABER, compression, distraction, thigh thrust, and Gaenslen. Three provocative test results are oftentimes required for a diagnosis. Other methods of diagnosis are also used, like X-rays, MRIs, and joint injections. Misdiagnosis: Nevertheless, although multiple methods exist to diagnose SIJ dysfunction, it is very commonly misdiagnosed. This is because the condition mimics symptoms of other conditions, and its etiology is overlooked. Treatment: When diagnosed, SIJ dysfunction can be treated through a range of measures. Either conservative treatments can be done, like physical therapy and NSAIDs, or more invasive procedures, such as surgical interventions, can be used to treat SIJ dysfunction. Conclusion: SIJ dysfunction is a prevalent, misdiagnosed condition that affects many individuals. This review highlights the importance of raising awareness among the public and clinicians to ensure an accurate diagnosis and treatment is given to patients.
WITHDRAWN: The multi-integrated DNA Bioinspired hydrogel with synergic effect of MB and AuNP with conductive, self-healing, and antibacterial properties as a wearable skin-like sensor
Authors: ELHAM elham , deigner Hans-Peter , faupel Franz , Tjardtsc Tim , daneshmand negin , altintase zynep 
Published: July 2024

Abstract

The full text of this preprint has been withdrawn by the authors as it was submitted and made public without the full consent of all the authors. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.
A Unified Framework for Systematic Curation and Evaluation of Aging Biomarkers
Authors: Moqri Mahdi , Ying Kejun , Paulson Seth , Eames Alec , Tyshkovskiy Alexander , Li Siyuan , Perez-Guevara Martin , Emamifar Mehrnoosh , Martinez Maximiliano Casas , Kwon Dayoon , Kosheleva Anna , Snyder Michael , Gobel Dane , Herzog Chiara , Poganik Jesse , Gladyshev Vadim 
Published: July 2024

Abstract

Aging biomarkers are essential for understanding and quantifying the aging process and developing targeted longevity interventions. However, validation of these tools has been hindered by the lack of standardized approaches for cross-population validation, disparate biomarker designs, and inconsistencies in dataset structures. To address these challenges, we developed Biolearn, an open-source library that provides a unified framework for the curation, harmonization, and systematic evaluation of aging biomarkers. Leveraging Biolearn, we conducted a comprehensive evaluation of various aging biomarkers across multiple datasets. Our systematic approach involved three key steps: (1) harmonizing existing and novel aging biomarkers in standardized formats; (2) unifying public datasets to ensure coherent structuring and formatting; and (3) applying computational methodologies to assess the harmonized biomarkers against the unified datasets. This evaluation yielded valuable insights into the performance, robustness, and generalizability of aging biomarkers across different populations and datasets. The Biolearn python library, which forms the foundation of this systematic evaluation, is freely available at https://Bio-Learn.github.io. Our work establishes a unified framework for the curation and evaluation of aging biomarkers, paving the way for more efficient and effective clinical validation and application in the field of longevity research.
Assessing ChatGPT 4.0’s Capabilities in The United Kingdom Medical Licensing Examination (UKMLA): A Robust Categorical Analysis
Authors: Casals-Farre Octavi , Baskaran Ravanth , Singh Aditya , Kaur Harmeena , Hoque Tazim Ul , Almeida Andreia , Coffey Marcus , Hassoulas Athanasios 
Published: July 2024

Abstract

Advances in the various applications of artificial intelligence will have important implications for medical training and practice. The advances in ChatGPT-4 alongside the introduction of the medical licensing assessment (MLA) provide an opportunity to compare GPT-4’s medical competence against the expected level of a United Kingdom junior doctor and discuss its potential in clinical practice. Using 191 freely available questions in MLA style, we assessed GPT-4’s accuracy with and without offering multiple-choice options. We compared single and multi-step questions, which targeted different points in the clinical process, from diagnosis to management. A chi-squared test was used to assess statistical significance. GPT-4 scored 86.3% and 89.6% in papers one-and-two respectively. Without the multiple-choice options, GPT’s performance was 61.5% and 74.7% in papers one-and-two respectively. There was no significant difference between single and multistep questions, but GPT-4 answered ‘management’ questions significantly worse than ‘diagnosis’ questions with no multiple-choice options (p = 0.015). GPT-4’s accuracy across categories and question structures suggest that LLMs are competently able to process clinical scenarios but remain incapable of understanding these clinical scenarios. Large-Language-Models incorporated into practice alongside a trained practitioner may balance risk and benefit as the necessary robust testing on evolving tools is conducted.
Functional anatomy and topographical organization of the frontotemporal arcuate fasciculus
Authors: Basile Gianpaolo Antonio , Nozais Victor , Quartarone Angelo , Giustiniani Andreina , Ielo Augusto , Cerasa Antonio , Milardi Demetrio , Abdallah Majd , de Schotten Michel Thiebaut , Forkel Stephanie J. , Cacciola Alberto 
Published: July 2024

Abstract

Traditionally, the frontotemporal arcuate fasciculus (AF) is viewed as a single entity in anatomo-clinical models. However, it is unclear if distinct cortical origin and termination patterns within this bundle correspond to specific language functions. We used track-weighted dynamic functional connectivity, a hybrid imaging technique, to study the AF structure and function in a large cohort of healthy participants. Our results suggest the AF can be subdivided based on dynamic changes in functional connectivity at the streamline endpoints. An unsupervised parcellation algorithm revealed spatially segregated subunits, which were then functionally quantified through meta-analysis. This approach identified three distinct clusters within the AF - ventral, middle, and dorsal frontotemporal AF - each linked to different frontal and temporal termination regions and likely involved in various language production and comprehension aspects.
Impact of Arteriovenous Fistula Closure on Cardiac and Renal Function in Renal Transplantation Patients
Authors: Tawfik Hisham Mostafa , Mohamed Mohamed Alaa El Dine , Shaarawy Mohamed Ahmed , Mohamed Mahmoud Ragab , Fathy Basma 
Published: July 2024

Abstract

Background: Due to the rapid expansion of numerous national and international transplantation programs, hemodialysis (HD) and peritoneal dialysis (PD) have become vital interim treatments for patients awaiting kidney transplantation.
Aim and objectives: Assessment of the effects of AV fistula ligation on cardiac and renal function in post-kidney transplant patients.
Patients and methods: A total of 98 kidney transplant recipients were divided into two groups: patients with closed arteriovenous fistula (AVF) (46) and patients with patent AVF (52). The study was done in outpatient nephrology clinics at Minia University and Minia Governorate Insurance Hospital.
Results: There was significant variation in terms of major and minor right-side diameter, IVC, PASP, MPAP, left ventricular hypertrophy, and left ventricular DD. In addition, there was a significant difference between the two groups regarding serum creatinine, urea, and eGFR.
Conclusion: AVF closure in renal-transplant patients can protect against severe cardiac changes and deterioration of eGFR.
Study on dynamic mechanical properties of steel fiber reinforced reactive powder concrete after high temperature
Authors: Feng Xinyu , Li Haiyan , Li Le , Fan Chengkun 
Published: July 2024

Abstract

This paper focuses on the dynamic mechanical properties of steel fiber reinforced reactive powder concrete (SFRPC) after high temperatures. Three kinds of reactive powder concrete (RPC) specimens with steel fiber volume fractions of 1%, 2% and 3% were prepared, and the impact compression tests of specimens treated at different temperatures (25℃, 200℃, 400℃, 600℃, 800℃) were carried out by Φ50 mm split Hopkinson pressure bar (SHPB). Accordingly, the dynamic stress-strain curves and various dynamic mechanical properties are obtained. Based on the modified Z-W-T constitutive model, the dynamic damage constitutive model of steel fiber reinforced RPC considering heating temperature and fiber content are derived to compare with the experimental results. The results show that the steel fiber has a significant effect on improving the deformation resistance and energy absorption capacity of RPC. The dynamic compressive strength shows strong strain rate dependence, and increase approximately linearly with the increase of average strain rate. High temperature has an obvious effect on the properties of RPC materials. The dynamic compressive strength, toughness and dynamic elastic modulus of RPC increase first and then decrease with the boundary of about 400℃. When the temperature reaches 800℃, the reinforcing effect of steel fiber is basically lost. The dynamic damage constitutive model curves coincide quite well with the stress-strain curves obtained from the test.
Influenza A Virus Employs Nei Endonuclease VIII-Like 1 (NEIL1) to Strength vRNP Function and Block IFN-β Production
Authors: Zhang Huixia , Li Changyan , Sun Ruiqi , Zhang Xinyi , Li Zexing , Hua Deping , Yin Boxuan , Yang Liu , Zhang Lilin , Huang Jinhai 
Published: July 2024

Abstract

Influenza A virus (IAV) has developed multiple tactics to hinder the innate immune response including the epigenetic regulation during IAV infection, but the novel epigenetic factors and their mechanism in innate immunity remain well studied. Here, through a non-biased high-throughput sgRNA screening of 1041 known epigenetic modifiers in a cellular model of IAV-induced interferon-beta (IFN-β) production, we identified nei endonuclease VIII-like 1 (NEIL1) as a critical regulator of IFN-β in response to viral infection. Further studies showed that NEIL1 promoted the replication of the influenza virus by regulating the methylation of cytonuclear IFN-β promoter (mainly CpG-345), inhibiting the expression of IFN-β and IFN-stimulating genes. The structural domains of NEIL1, especially the catalytic domain, were critical for the suppression of IFN-β production, but the enzymatic activity of NEIL1 was dispensable. Furthermore, our results revealed that NEIL1 relied on interactions with the N- and C-terminus of the nucleoprotein (NP) of IAV, and NEIL1 expression facilitated the entry of the NP into the nucleus, which further enhanced the stability of the viral ribonucleoprotein (vRNP) complex and thus contributed to IAV replication and transcription. These findings reveal an enzyme-independent mechanism of host NEIL1 that negatively regulates IFN-β expression, thereby facilitating IAV propagation. Our study provides new insights into the roles of NEIL1, both in directly promoting virus replication and in evading innate immunity in IAV infection.
A comparative analysis of fault detection and process diagnosis methods based on a signal processing paradigm
Authors: Aiordachioaie Dorel 
Published: July 2024

Abstract

An important paradigm in industrial engineering for fault detection and diagnosis purposes is signal processing. The various methods consider methods in the time, frequency or time-frequency domain for signal processing as state and output signals from the considered process. The objective of this work is to perform a comparative analysis of the most commonly used methods based on a signal processing paradigm and in the context of fault detection and process diagnosis. The electromechanical equipment that generates mechanical vibrations—as an effect of bearing faults—is considered and analyzed. The recorded data are explored with smaller and sliding frames, adapted to the processing criteria used. Seven methods are considered for evaluation: two in the time domain, two in the frequency domain and three in the time-frequency domain. The main problem is to extract and select the right features to use in the classification stage. The methods of the time domain are based on statistical moments and signal modeling. The methods in the frequency domain use either the discrete components of power spectra or the features of the frequency domain. In the time-frequency domain, the coefficients of the time-frequency transforms define digital images, which are further processed. For testing, the methods are evaluated with real recorded data from bearings with several types and sizes of faults, i.e., incipient, medium, advanced, and large. Finally, the considered methods are compared from the point of view of five criteria, namely, the recognition rate, window length, response time, computational resources, and complexity of the algorithms. A global quality criterion is built and used to assess the quality of the methods. The computer-based simulation results show acceptable performance for all methods for the test case of bearings but the potential to detect more complex faults and change detection in the behavior of the machines, in general. Time-frequency methods offer an optimum.
Support-absorption composite clamping static response prediction and clamping deformation suppression
Authors: Fang Rui , Liu Haibo , Zhao Jiulong , Chen Ran , Chai Xingliang , Bo Qile , Li Te , Wang Yongqing 
Published: July 2024

Abstract

Thin-walled spherical shells are weakly rigid and prone to clamping deformation under clamping force, which will affect machining accuracy. In this paper, the support-absorption composite clamping method is proposed and the in-situ conformal clamping strategy is obtained through the deformation coordination optimization. Firstly, the thin-walled spherical shell static response model is established, and the displacement analytic solution of equivalent constraint superposition is proposed by decoupling load and boundary constraint and Reisner's force-displacement hybrid method. Then, the vacuum generation of the Laval nozzle and pressure regulation mechanism is elucidated, and the matching mechanism of vacuum degree and spring support is revealed. Considering the support and adsorption deformation coordination optimization, the in-situ conformal clamping model is constructed. Next, the simulation explores the response of thin-walled spherical shells at different positions and adsorption effects on different wall thicknesses. The applied velocity ratio of the load in in-situ conformal clamping is analyzed. Finally, comparative experiments with different clamping methods are carried out and the results show that: Larger deformation in the top ± 10° range. The average prediction error of the theoretical model is 11.97%. With a larger load, the larger deformation, and recommended to control within 0.5Mpa. A larger number of partitions isn't recommended, nonlinearities could cause larger acceleration mutations. The thinner the thickness or the smaller the support load, the support-adsorption composite clamping effect is more obvious, the maximum can reduce the clamping deformation by 64.3%. In-situ conformal clamping method can reduce the deformation of the clamping process by 33.3%.
Retrospective analysis of Vogt-Koyanagi-Harada’s recurrence within a case series of nineteen patients followed between 2003 and 2018 in an academic center
Authors: Kozyreff Alexandra , Bughin Alice , Lefebvre Chantal , Pothen Lucie , Yildiz Halil 
Published: July 2024

Abstract

Purpose: to define a timeframe of recurrences according to the clinical presentation of the inflammation and to the course of the disease. This could influence the final visual acuity and avoid ocular complication such as cataract, glaucoma, choroidal neovascularization, subretinal fibrosis or fundus depigmentation.
Material and methods: retrospective study of nineteen patients affected of Vogt-Koyanagi-Harada disease followed between 2003 and 2018.
Results: within our case series, 53% of our patients had no recurrence during a follow-up up to one hundred and sixty-eight months. Among the nine patients presenting a recurrence, five had at least one episode of posterior inflammation, one exhibited anterior and posterior recurrence, and five developed at least one recurrence in anterior structures.
According to the Kaplan Meier’s method, the overall survival without any recurrence at three months is equal to 68% ± 11%. All posterior segment inflammatory relapses occurred within three months and a half of initiation of systemic treatment. On the other hand, the timeline of anterior recurrence is more scattered. They appeared between two and thirty-seven months.
This careful follow-up distinguishing the type of inflammatory recurrence made it possible to find final visual acuity greater than or equal to 9/10 (equivalent ≥ 20/25), with the exception of one amblyopic eye.
Conclusion: The chronological occurrence of inflammatory episodes is earlier posteriorly than anteriorly. A posterior recurrence does not expose to a higher risk of anterior inflammation relapse during the follow-up. This distinction is important for understanding understandig the course of the disease. In fact, the differentiation between the initial acute phase (mainly posterior inflammation) and chronic recurrences (granulomatous anterior segment inflammation) allows better adaptation of systemic therapy and better visual prognosis in the long term.
The potential of short-wave infrared hyperspectral imaging and deep learning for dietary assessment: a prototype on predicting closed sandwiches toppings
Authors: Kok Esther , Chauhan Aneesh , Tufano Michele , Feskens Edith , Camps Guido 
Published: July 2024

Abstract

Accurate measurement of dietary intake without interfering in natural eating habits is a long-standing problem in nutritional epidemiology. We explore the applicability of hyperspectral imaging and machine learning for dietary assessment of home-prepared meals, by building a proof-of-concept which automatically detects food ingredients inside closed sandwiches. Individual spectra were selected from 24 hyperspectral images of assembled closed sandwiches, preprocessed with SNV-filtering, derivatives, and subsampling, and fed into a multilayer perceptron. The resulting models had an accuracy score of ~ 80% prediction of the type of bread, ~ 60% for predicting butter, and ~ 24% for filling type. Further analysis on non-homogeneous mixed food items, using computer vision techniques, will contribute towards a generalizable system. While there are still significant technical challenges to overcome before such a system can be routinely implemented in studies of free-living subjects, we believe it holds promise as a future tool for nutrition research and population intake monitoring.