bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rotator cuff tendinopathy: frequency and factors associated with response to medical treatment
Authors: ZABSONRE Wendlassida Joelle Stéphanie TIENDREBEOGO , Tiaho Eric , M’Ba Cyrille , Kaboré Fulgence , Ouédraogo Aboubakar , Zongo Enselme , Compaoré Irénée , Ouédraogo Dieu-Donné 
Published: April 2024

Abstract

Background
Rotator cuff tendinopathy (RCT) is a generic term for degenerative or traumatic lesions of the rotator cuff tendons. It represents a major public health challenge, with significant economic consequences due to work stoppages. The purpose of the study was to evaluate the frequency and factors associated with response to medical treatment of rotator cuff tendinopathy (RCT).
Methods
This was a descriptive and analytical cross-sectional study conducted over a 7-month period (from 1 January 2023 to 31 July 2023). Patients treated for RCT during this period were included, while those with RCT associated with other shoulder pathologies or who had undergone shoulder surgery were excluded. The Constant-Murley score was used for clinical assessment of the shoulder at baseline (S0) and at the end of treatment (S4).
Results
Eighty-two patients were included. The mean age was 57.27 ± 13.1 years. The sex ratio was 0.86, with 44 (53.66%) women. The mean duration of symptoms at the time of diagnosis was 10.46 months ± 5.54. Sixty-three (76.8%) patients had a high level of manual effort. Sixty-eight (82.9%) patients had tendinopathy of the supraspinatus muscle. Tendon rupture was more frequent in older patients (P < 0.001). Twenty-seven (81.81%) patients with tendon rupture were also severely limited at S0 (P = 0.001). Thirty-six (43.9%) patients received functional rehabilitation and a further 28 (34.15%) local corticosteroid injections. Eight (72.70%) of the 11 patients who received combined medical treatment (injections and rehabilitation) showed an overall improvement in the Constant-Murley score of between 50 and 80 points at S4 (P = 0.016).
Conclusion
Manual strain, advanced age and the presence of tendon rupture were associated with a poor functional prognosis. A statistically significant association was found between Constant score and combined medical treatment.
Evaluating the Agreement between Human Preferences, GPT-4V and Gemini Pro Vision Assessments: Can AI Recognise Which Restaurants People Might Like?
Authors: Krupić Dino , Matijević Domagoj , Šuvak Nenad , Ševerdija Domagoj , Maltar Jurica 
Published: April 2024

Abstract
The study aims to introduce a methodology for assessing agreement between AI and human ratings, specifically focusing on visual large language models (LLMs). It presents empirical findings on the alignment between ratings generated by GPT-4 Vision (GPT-4V) and Gemini Pro Vision with human subjective evaluations of environmental visuals. Using photographs of restaurant interior design and food, the study estimates the degree of agreement with human preferences. The intraclass correlation reveals that GPT-4V, unlike Gemini Pro Vision, achieves moderate agreement with participants’ general restaurant preferences. Similar results are observed for rating food photos. Additionally, there is good agreement in categorizing restaurants into low cost-exclusive categories based on interior quality. Overall, GPT-4V currently demonstrates limited ability in providing meaningful ratings of visual stimuli compared to human ratings and performs better in this task compared to Gemini Pro Vision.
Arbuscular mycorrhizal fungi affect early phenological stages of three secondary vegetation species in a temperate forest
Authors: Vázquez-Santos Yasmin , Castillo-Argüero Silvia , Montaño Noé Manuel , Espinosa-García Francisco Javier , Flores-Ortiz César Mateo , Martínez-Orea Yuriana 
Published: April 2024

Abstract

The relationship between arbuscular mycorrhizal fungi (AMF) and secondary vegetation (SV) species at early phenological stages is critical for the successful establishment of these plants on disturbance sites in temperate forests. The main objective of this research is to evaluate the effect of AMF colonization on the early phenological stages (germination and early growth) of three shrub species present in the SV of a temperate forest in central Mexico. We collected soil from different sites in theAbies religiosaforest in central Mexico. We collected seeds ofAcaena elongata,Ageratina glabrata, andSolanum pubigerum. We used a controlled experimental design with pasteurized soil (-AMF treatments) and unpasteurized soil (+ AMF treatments). We monitored germination percentage, growth (shoot and root weight and total biomass), AMF root colonization, and the mycorrhizal response index (MRI) for each plant species. All three species tested benefited by AMF, showing higher germination rates. Shoot and root weight and total biomass were significantly higher in the + AMF treatment.Solanum pubigerumshowed greater stem length andAgeratina glabratashowed greater root development due to AMF.Ageratina glabrataandAcaena elongatawere the most responsive to AMF as indicated by MRI. This research underscores the critical role of AMF in the early phenological stages of SV and highlights the potential ecological benefits of AMF in supporting plant germination and plant growth. This information suggests the integration of mycorrhizal inoculation into restoration practices to enhance ecological resilience in temperate forest ecosystems.
Quinoa Proteins Isolate, a Candidate for Functional Ingredients Design
Authors: Rubinstein Alejandra , Pérez Oscar E. 
Published: April 2024

Abstract
The objective of the present contribution was to design and characterize resveratrol (RSV) and tocopherol (TOC) loaded quinoa protein (QP) nanocomplexes, their antioxidant and antiradical functionality were also evaluated. QP intrinsic fluorescence spectra showed a quenching effect exerted by RSV and TOC, demonstrating protein-bioactive compounds interactions. Stern-Volmer and Scatchard models application confirmed the static quenching effect and allowed to obtain parameters that described the QP-RSV or QP-TOC complexation process. Isothermal titration calorimetry allowed obtaining thermodynamic parameters to describe the interaction between RSV or TOC with QP. Protein aggregates up to 40 nm in diameter were induced by bioactive compounds as detected by atomic force microscopy. QP-RSV and QP-TOC nanocomplexes showed additive effect in their antioxidant capacity. These nanocomplexes could constitute a real platform for the design of functional ingredients.
A Pothole Can Be Seen with Two Eyes: An Ensemble Approach to Pothole Detection
Authors: Patawar Atharv , Mehdi Mohammed , Kore Bhaumik , Saval Pradnya 
Published: April 2024

Abstract
The issue of potholes and bad road quality is faced by nearly every developing country. These conditions often lead to accidents and traffic and cause the general public inconvenience. Significant research work has been performed in the field of effective pothole and road quality detection but due to several underlying issues like relying on only computer vision or sensor-based modeling, or requiring specialized equipment like LiDAR, implementing these solutions in the real world has never been feasible, especially for developing countries where a reliable system is required which works under any condition and more importantly, can be implemented with minimal resources and changes to the existing infrastructure. The proposed system is an end-to-end robust architecture that utilizes mobile devices mounted on government vehicles for data collection and features an innovative ensemble of a YOLOS and a YOLOv8 model resulting in a 97.34% mAP@0.50 score for pothole detection, in conjunction with state-of-the-art sensor based pothole detection and road quality detection models resulting in impressive accuracies of 98.5% and 95.4% respectively. This two-forked approach to pothole and road quality detection combined with innovative connected applications like an analytics dashboard for the government and a navigation application for the consumer make this entire system highly relevant while being scalable, reliable, and easily deployable using the existing infrastructure in developing countries.
Model-based Adversarial Imitation Learning with Self-adatpive Error Control
Authors: Wang Yi , Gong Shengrong , Du Xin , Zhong Shan , Si Yali 
Published: April 2024

Abstract
Generative Adversarial Imitation Learning (GAIL) presents the ability to learn policies without prior knowledge of the underlying reward function. However, it often suffers from limited sample efficiency due to its reliance on reinforcement learning for policy learning, mandating extensive real-time interactions with the environment. To address this challenge, this paper introduces a refined framework named TM-GAIL, which combines transition function model learning with GAIL. This approach capitalizes on the utility of neural networks to construct a transition function model, facilitating the generation of virtual samples to complement real data. The training of the discriminator is augmented by the inclusion of virtual samples alongside expert demonstration data. In the context of policy learning, the incorporation of virtual samples, real samples, and the reward derived from the discriminator enriches the policy learning. Furthermore, a self-adaptive error control module has been meticulously designed for the regions characterized by high returns and to mitigate model errors. Empirical findings demonstrate that TM-GAIL significantly improves sample efficiency in comparison to imitation learning and model-free methods. It achieves performance levels that closely align with those of domain experts across both continuous and discrete tasks.
Relationship estimation of hardened Concrete properties using SPSS for modified concrete with sustainable materials
Authors: Bahoria B. V. , Vairagade V. S. , Nandurkar B. P. , Raut J. M. 
Published: April 2024

Abstract
The aim of this study is to investigate the potential of quarry dust and waste plastic as replacements for conventional sand in concrete, with a focus on sustainability. Sustainable utilization involves maximizing the effectiveness of quarry dust while minimizing environmental impact. Concrete mixes were prepared using ordinary river sand and varying percentages of quarry dust in combination with waste plastic. Notably, the inclusion of quarry dust with waste plastic significantly improved the concrete's strength. Regression analysis, conducted using SPSS software, was employed to predict the compressive strength of the concrete at different curing durations (7, 14, 28, and 90 days). The analysis revealed strong correlations between the variables, enabling the development of predictive models. These models were validated, and the results demonstrated that the addition of quarry dust, alongside waste plastic, positively influences the mechanical properties of concrete. Overall, this study highlights the efficacy of SPSS software in analyzing and predicting concrete strength, thus contributing to the advancement of sustainable construction practices.
Dynamic Variational Quantum Eigensolver: Incorporating Time-evolution for Ansatz Design and Ground State Simulation
Authors: Wang Rui , Zhao Runsheng , Ji Yuxin , Cheng Tao , Fan Xingkui , Ma Hongyang 
Published: April 2024

Abstract

Variational Quantum Eigensolver (VQE) addresses challenges that conventional computation struggles to overcome. However, VQE lacks the ability to autonomously trend towards the direction of quantum advantage, leading to unnecessary consumption of time and resources during parameter optimization. In this work, we present a Simulating Dynamic VQE (D-VQE) that incorporates time evolution for achieving desired simulation accuracy and parameter optimization. Introducing causal cones for Parameterized Quantum Circuits (PQC) and establishing dynamic judgment rules. Consequently, we can reduce the overstacking of components in PQC ansatz. Based on the requirements of precision and circuit scale, a reasonable operator pool is set to deal with the parameters. Through numerical experiments, our method effectively simulates the search for the ground state in the transverse-field Ising model, achieving a relative energy error below 10^(-3) and improving ground state approximation capability. Moreover, in the context of optimized Boltzmann machine learning, the Kullback-Leibler divergence (KLD) value converges to 0.03. These results prove that our work provides an effective and feasible consideration for the improvement of variational quantum algorithms.
Understanding Cancer Disparities among African Americans in Los Angeles
Authors: Chintala Srikar , Sjogren-Black Charlie , Tang Willis 
Published: April 2024

Abstract

Background: In Los Angeles (LA), African Americans face significant disparities in cancer outcomes, particularly in prostate, breast, cervical, colorectal, and lung cancers. Addressing these disparities requires a comprehensive understanding of the root causes and effective interventions tailored to African American communities.
Methods: This paper employs a systematic review methodology to analyze existing literature on cancer disparities among African Americans in LA. A comprehensive search of the PubMed database was conducted the following keywords and other relevant synonyms: cancer, African American, and LA. Studies published up till March 2024 were included for review. The 21 (of 221) articles within our inclusion criteria that measured cancer disparities for African Americans within Los Angeles were retained.
Results: Among 21 articles that met inclusion criteria, prostate cancer was the most frequently examined type. The data had a significant focus on screening, treatment, survival, and research related to cancer disparities among African Americans in LA. Interventions aimed at reducing disparities often involved community health advisors or patient-centered care, with a focus on interventions within African American churches. Factors contributing to cancer disparities included geography, culture, socioeconomic status, and healthcare quality and inclusion.
Conclusions: Addressing cancer disparities among African Americans in LA necessitates a multifaceted approach. Economic, geographic, and cultural factors, alongside limited clinical trial participation, contribute to these disparities. Prioritizing culturally sensitive healthcare, promoting education, fostering community trust, and advocating for systemic changes are crucial steps. By targeting these root causes, progress toward health equity in cancer care for African Americans can be achieved.
A fast three-dimensional measurement method based on color fringe projection and background intensity calibration
Authors: Zhu Qian , Du Hubing , Tang Bo , Ma Yueyang 
Published: April 2024

Abstract

Phase-shifting profilometry (PSP) is one of the most widely available methods in three-dimensional (3D) measurement. However, PSP is not suitable for dynamic measurements due to multiple projections. The color fringe projection profilometry(CFPP) can encode three grayscale fringe patterns in a single color pattern, preserving the robustness of PSP while enabling dynamic measurements. But for the CFPP measurement system, color coupling and imbalance phenomena are inevitable between the RGB channels, which increases the measurement error. This paper proposes a background intensity calibration (BIC) method to correct the color imbalance and reconstruct 3D shapes by a single-shot projected-captured. First, capture a color fringe image and extract the background intensity by searching the upper and lower envelopes to get three background-free fringe images; Secondly, solve the normalized coefficient to balance the three background-free images. As a result, a color fringe image can be split into three phase-shifting fringe images with the normalized modulation intensity and good sinusoidal aiming to perform phase demodulation by three-step PSP; Thirdly, the demodulation phase is unwrapped using a simple solving fringe orders algorithm based on a positive and negative binarization (PNB) method. Several experiments on dynamic scenes were performed, verifying that the measurement speed and accuracy of the proposed BIC method are not limited by the object moving, which can achieve fast, dense, and accurate 3D measurements.
Image Classification for Defect Detection of Light Aircraft
Authors: Connolly Luke , Garland James , O'Gorman Diarmuid , Tobin Edmond 
Published: April 2024

Abstract

Visual inspections of aircraft are a vital part of routine procedures for maintenance personnel in the aviation industry. However, visual inspections take up a considerable amount of time to perform and are susceptible to human error. To mitigate this, utilising image classification for detecting defects is proposed. This approach utilises transfer learning of ResNet-50 within MATLAB to determine whether a defect is present in an image taken of the aircraft. The proposed method offers a solution for improving the efficiency and accuracy of defect detection during a general visual inspection in the aviation industry. Targeted defects here are damaged_skin and missing_rivets alongside a class denoting no_defect. Validation and testing accuracies achieved in this study are 88.33 % and 65.55 %, respectively.
Selection and Guidance: High-dimensional Identity Consistency Preservation for Face Inpainting
Authors: li qian , Zhan Xin , Li Haibin , zhang wenming 
Published: April 2024

Abstract

This paper primarily investigates the issue of identity inconsistency resulting from facial inpainting. In the current facial image inpainting process, most low-frequency information is learned directly from the uncovered areas, while high-frequency information, including texture details, is generated from the dataset. The averageness of low-frequency features and the unreliability of high-frequency features result in identity deviations in the inpainted faces. To address this problem, a two-stage generative model is proposed, which includes structural prior guidance and multidimensional consistency guidance. Firstly, a parsing inpainting module was designed to predict structural information. Subsequently, a multidimensional information guidance module was constructed, which, based on semantic consistency guidance, extracts low-frequency confidence information of the inpainted image to suppress the averageness of facial inpainting. Frequency-domain information is extracted from the inpainted image, combined with a facial recognition network, and the frequency-domain identity feature consistency loss is calculated to aid in the inpainting of high-frequency information, including identity features, thus achieving identity consistency in facial inpainting. Furthermore, to evaluate the consistency of the identity information of inpainted faces and real, identity features generated by the inpainting network are extracted, and the distribution of these features is utilized as a measure of inpainting quality. We conducted experiments on the CelebAMask-HQ dataset, and both qualitative and quantitative studies indicate that our proposed algorithm outperforms state-of-the-art methods.
A new kind of hierarchical porous zirconium phosphonate: preparation and application on oxidation catalysis
Authors: Fu Shan , Tian Yi , Long Xin , Shao Qian , Wang Kefeng , Lei Junyu , Hao Haijun , Xu Qinghong 
Published: April 2024

Abstract

A kind of new zirconium phosphonate material (named as ZrDP) with multilevel porous structure and high surface area (about 408.6 m2/g) was synthesized by the reaction between 1,4,7,10-Tetraazacyclododecane-1,4,7,10-tetrayl- tetrakis(methylphosphonic acid) (DOTMP) and zirconium dichloride oxide octahydrate. Microporous structure (diameter about 0.64 nm) from 1,4,7,10- Tetraazacyclododecane in DOTMP and structural pores with diameter about 1.68 nm were found in the material. A series of metal coordination structures were synthesized basing on the coordination skeleton in ZrDP and Cu@ZrDP (Cu2+ ions coordinated with N atoms in ZrDP) exhibited high catalytic activity in the selective oxidation reaction from benzyl alcohol to benzaldehyde with 90.2% selectivity.
Modulation of Astroglial Glutamate Transporters by CB1 Receptor Shapes Endocannabinoid-Mediated Long-Term Depression in the Medial Prefrontal Cortex
Authors: Vaz Sandra , Gonçalves-Ribeiro Joana , Rodrigues-Freitas Leandro , Nanclares Carmen , Sebastião Ana , Araque Alfonso 
Published: April 2024

Abstract
Excitatory Amino Acid Transporters (EAATs), prominently expressed in astrocytes, are dynamic proteins crucial for synaptic function and plasticity, notably in long-term depression (LTD). However, the precise adaptations in glutamate uptake during LTD remain elusive. Within the medial prefrontal cortex (mPFC), endocannabinoid (eCB) signaling assumes a central role in synaptic plasticity, ultimately affecting memory and mood regulation. In astrocytes, CB1R activation increases intracellular Ca2+. We therefore hypothesize that astroglial CB1R could shape eCBD-LTD through EAATs modulation. By performing ex vivo Ca2+ imaging and electrophysiological recordings we could conclude that LTD in mPFC is astroglial Ca2+-dependent, through a mechanism that involves a CB1R-mediated inhibition of glutamate transport activity. Importantly also, we were able to rescue LTD under deficient Ca2+ levels in astrocytes. Our findings provide evidence that CB1R-mediated decrease of EAATs activity through astroglial Ca2+-dependent mechanism is crucial for LTD maintenance.
A computational Analysis of the Proton Affinity and the Hydration of TEMPO and Its Piperidine Analogs
Authors: Shiroudi Abolfazl , Śmiechowski Maciej , Czub Jacek , Abdel-Rahman Mohamed A. 
Published: April 2024

Abstract
The study investigated the impact of protonation and hydration on the geometry of nitroxide radicals using B3LYP and M06-2X methods. Results indicated that TEMPO exhibited the highest proton affinity in comparison to TEMPOL and TEMPONE. Two pathways contribute to hydrated protonated molecules. TEMPONE shows lower first enthalpies of hydration (ΔH1-M), indicating stronger H-bonding interactions, while TEMPO shows higher values, indicating weaker interactions with H2O. Solvent effects affect charge distribution by decreasing their atomic charge. Spin density (SD) is primarily concentrated in the NO segment, with minimal water molecule contamination. Protonation increases SD on N-atom, while hydration causes a more pronounced redistribution for water molecules. The stability of the dipolar structure (>N·+-O-) is evident in SD redistributions. The frontier molecular orbital (FMO) analysis of TEMPONE reveals a minimum EHOMO-LUMO gap (EH-L), enhancing the piperidine ring's reactivity. TEMPO is the most nucleophilic species, while TEMPONE exhibits strong electrophilicity. Transitioning from NO radicals to protonated forms increases the EH-L gap, indicating protonation stabilizes FMOs. Increased water molecules make the molecule less reactive, while increasing hydration decreases this energy gap, making the molecule more reactive. A smaller EH-L gap indicates the compound becomes softer and more prone to electron density and reactivity changes.