bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anti-chondrogenic role of nerve growth factor in osteoarthritis and human induced pluripotent stem cells-derived chondrogenesis model
Authors: Jung Se In , Rim Yeri Alice , Choi Si Hwa , Kim Jang-Woon , Ju Ji Hyeon 
Published: September 2023

Abstract
Background
Nerve growth factor (NGF) is a neurotrophic factor involved in the survival, differentiation, and growth of sensory neurons and nociceptive function. Additionally, it has been suggested to play a role in osteoarthritis (OA). Previous studies have reported a relationship between NGF and OA; however, the underlying mechanisms remain unknown. Therefore, we investigated the relationship between cartilage characteristics and NGF expression in the pathology of OA using human induced pluripotent stem cells (hiPSCs)-derived chondrogenic pellets.
Methods
Synovial fluid was collected from patients (n = 3) with OA. NGF expression was confirmed in human OA cartilage tissue and synovial fluid. To confirm the role of NGF in chondrocalcinosis during OA development, hiPSCs-derived chondrogenic pellets were treated with NGF during differentiation. The expression of chondrogenic and hypertrophic (osteogenic) markers was confirmed using polymerase chain reaction and western blotting. Additionally, the expression of inflammatory cytokines and matrix metallopeptidase (MMP) was confirmed.
Results
NGF treatment decreased the expression of chondrogenic markers (SOX9, aggrecan, and collagen type II, alpha 1) in chondrogenic pellets, whereas the expression of hypertrophy markers (collagen type X, alpha 1 and vascular endothelial growth factor A) was increased. The expression of inflammatory cytokines and MMPs also increased in NGF-treated chondrogenic pellets.
Conclusions
These findings suggest that increased NGF levels may induce chondrocalcinosis and osteophyte formation during OA progression and may represent a potential target for OA treatment.
New Ranking Approach of Intuitionistic Fuzzy Sets and its Application in Cognitive Transportation Problem
Authors: Saikia Bornali , Dutta Palash 
Published: September 2023

Abstract
In real-life problems, we frequently face uncertain situations because of human cognitive behaviour. Researchers have suggested meticulous mathematical notions to tackle such situations since its initiation. An intuitionistic fuzzy set is one of the effective extensions of a fuzzy set. Intuitionistic fuzzy sets have been applied in various real-life cognitive decision-making problems, for instance, engineering, medicine, pattern recognition, transportation, criminal investigation, etc. Numerous research works can be found in the literature, and most had several restrictions or were performed as unfit for providing human satisfaction outcomes. This work proposes a way to rank intuitionistic fuzzy sets using membership and non-membership functions. We discuss the benefits and provide examples to illustrate the approach. Then, we use our proposed ranking approach to deal with cognitive transportation problems, as it is well known that the core objective of transportation problems is to find optimal solutions. The literature contains various research studies on intuitionistic fuzzy problems with transportation. However, most of them have drawbacks.. Some methods are impractical, and others can't meet supply and demand limitations.. As a result, a method has been developed to lessen restrictions on solving methods of the intuitionistic fuzzy transportation problem. Although, some existing transportation problems are depicted in this work for a comparative study to elaborate on the significance of the present work. Our work deals with solving transportation problems in different uncertain situations using intuitionistic fuzzy environments like normal mixed type triangular, fully triangular and generalized trapezoidal intuitionistic fuzzy.. At the end of the study, hesitancy, cost effectiveness, statistical significant, sensitivity, result analysis, computational complexity and advantages are discussed to establish the effectiveness of the proposed work.
Protective effects of IL18-105G&gt;A and IL18-137C&gt;G genetic variants on severity of COVID-19
Authors: Mori Mayara Tiemi Enokida , Simão Andrea Name Colado , Danelli Tiago , Oliveira Sayonara Rangel , Cassela Pedro Luis Candido Souza , Trigo Guilherme Lerner , Cardoso Kauê , Tejo Alexandre Mestre , Tano Zuleica Naomi , de Almeida Elaine Regina , Reiche Edna Maria Vissoci , Maes Michael , Lozovoy Marcell Alysson Batisti 
Published: September 2023

Abstract
Objective and Design:
A cross-sectional study evaluated the IL18-105G > A (rs360717) and IL18-137C > G (rs187238) variants on Coronavírus Disease 2019 (COVID-19) severity.
Subjects and Methods:
528 patients with COVID-19 classifed with mild (n = 157), moderate (n = 63) and critical (n = 308) disease were genotpyed for the IL18-105G > A and IL18-137C > G variants.
Results
The IL18-105G > A was associated with severe disease (moderate + critical), with effects of the GA genotype in the codominant [Odds ratio (OR), (95% confidence interval) 0.55, 0.34–0.89, p = 0.015], overdominant (0.56, 0.35–0.89, p = 0.014) and the AA + GA genotypes in the dominant (0.60, 0.38–0.96, p = 0.031) models. The IL18-137GC was also associated with severe disease with effects in the codominant (0.55, 0.34–0.89, p = 0.015), and overdominant models (0.57, 0.36–0.91, p = 0.018), and the GG + CG genotypes in the dominant model (0.59, 0.37–0.93, p = 0.025). IL18-105 GA coupled with age, chest computed tomograhy scan anormalities, body mass index, heart diseases, type 2 diabetes mellitus, hypertension, and inflammation may be used to predict the patients who develop severe disease with an accuracy of 84.3% (sensitivity: 83.3% and specificity: 86.5%).
Conclusion
The IL18-105G > A and IL18-137C > G variants contribute to COVID-19 severity and the effects of IL18-137C > G may be modulating IL-18 production and Th1-mediated immune responses.
Facile synthesis and multiple application of ultralong-afterglow room temperature phosphorescence aggregate carbon dots from simple raw materials
Authors: Zhu Wenping , Wang Like , Yang Weijie , Chen Yahong , Liu Zengchen , Li Yanxia , Xue Yingying 
Published: September 2023

Abstract
Owing to the ultralong afterglow, room temperature decay phosphorescence nanomaterials have aroused enough attention. In the work, by simple one-pot solid-state thermal decomposition reaction, aggregate carbon dots (CDs) was prepared from trimesic and boric acid. Based on the intermolecular hydrogen bonds and intramolecular π-π stacking weak interaction from precursors, CDs was encapsulated in boron oxide matrix and formed aggregation. The aggregate state of CDs facilitated the triplet excited states (Tn), which could induce the room temperature decay phosphorescence properties. By careful investigation, under different excitation wavelengths at 254 nm and 365 nm, the aggregate CDs showed > 15 s and > 3 s room temperature phosphorescence emission in the naked eye, which was associated with 1516.12 ms and 718.62 ms lifetime respectively. And the aggregate CDs exhibited widespread application in encoding encryption, optical anti-counterfeiting and fingerprint identification etc. The interesting aggregate CDs revealed unexpected ultralong-afterglow room temperature decay phosphorescence properties and the work opened a window for constructing ultralong-afterglow room temperature decay phosphorescence aggregate CDs nanomaterials.
Transition of Care: Lessons from the Standardizing Care to Improve Outcomes in Pediatric End Stage Renal Disease (SCOPE) Dialysis Collaborative
Authors: Munshi Raj , Torres Alison Hewitt , Ramirez-Preciado Bertha , Reyes Laura J Castellanos , Richardson Troy , Pruette Cozumel S 
Published: September 2023

Abstract
Acknowledging the importance of preparing the pediatric dialysis patient for successful transfer to an adult provider, centers from the Standardizing Care to Improve Outcomes in Pediatric End Stage Renal Disease (SCOPE) Dialysis Collaborative developed transition tools and performed iterative implementation of a transition of care program to gain real life insight into the drivers and barriers towards implementation of a transition program for patients receiving dialysis. 9 educational modules, along with introductory letter and assessment tool were created. A 4-month pilot implementation study among 6 centers of varying patient population (age ≥ 11 years) was performed. TOC tools were further refined and broader implementation within the collaborative was performed. Interim assessment of TOC tool utilization and implementation success was performed among 11 centers, forming the foundation towards a broader discussion regarding process, barriers and success towards TOC implementation among 26 centers. Transition champion was a key driver of successful implementation. Lack of institutional support and collaboration with adult dialysis centers were important barriers towards sustainability. COVID pandemic and increased staff turnover affected longer term implementation of TOC program. Successful transition and transfer of AYA with ESKD on dialysis remains a challenge. This study represents the experience of the largest cohort of pediatric dialysis centers, with diversity in population size and geography, towards development and implementation of a TOC program. The collaborative adds to the resources available to assist a center towards transition and transfer, with particular focus on transitioning patients on dialysis.
Bilingual Hate Speech Detection on Social Media : Amharic and Afaan Oromo
Authors: Ababu Teshome Mulugeta , Woldeyohannis Michael Melese , Getaneh Emuye Bawok 
Published: September 2023

Abstract

Due to significant increases in internet penetration and the development of smartphone technology during the preceding couple of decades, many people have started using social media as a communication platform. Social media has grown to be one of the most significant components, with several benefits. However, technology also poses a number of threats, challenges, and barriers, such as hate speech, disinformation, and fake news. Hate speech detection is one of the many ways social media platforms can be accused of not doing enough to thwart hate speech on their platform. People in Bilingual and multinational societies commonly employ a code mix in both spoken and written communication. Among these, Amharic and Afaan Oromo language speakers frequently mix the two languages when conversing and posting on social media. The majority of previous study concentrated on identifying either technological favoured language or monolingual hate speech in Ethiopian languages; however, the availability of Bilingual communication in social media hampers the propagation of hate speech via social media. In this work, a Bilingual hate speech detection for Amharic and Afaan Oromo languages were conducted using four different deep learning classifiers (CNN, BiLSTM, CNN-BiLSTM, and BiGRU) and three feature extraction (Keras word embedding, word2vec, and FastText) techniques. According to the experiment, BiLSTM with FastText feature extraction is an outperforming the other algorithm by achieving a 78.05\% percent of accuracy for Bilingual Amharic Afaan Oromo hate speech detection. The FastText feature extraction overcomes the problem of out of vocabulary (OOV). Furthermore, we are working towards including others linguistic features of the languages to detect hate speech and make the resource available to facilitate further research in the area of Bilingual hate speech detection for other under-resourced Ethiopian languages.
A Re-evaluation of Amputations versus Rotationplasties in the Reconstruction of Tumors about the Knee
Authors: Tud Abigail Rivera , Singh Tanveer , Nathan Saminathan Suresh 
Published: September 2023

Abstract
Background
Rotationplasties are considered superior to above knee amputations (AKA) in the reconstruction of tumor-ablated limbs. We compared both procedures performed for patients with musculoskeletal tumors about the knee, to answer the following:
1. Are subjective functional outcomes among knee rotationplasty (KRP) patients superior to above knee amputees?
2. Are objective gait parameters of above knee amputees inferior to rotationplasty patients?
Methods
We evaluated 19 patients who had undergone AKA or KRP for distal femur or proximal tibia tumors. Four underwent AKA, while 7 had KRP. Patients were assessed using motion capture and force plate array analysis. Subjective function was assessed using the Musculoskeletal Tumor Society (MSTS) Score.
Results
Ten males and 9 females were followed an average 4.0 ± SD5.5 years. Mean age was 31 ± SD10 years. Above-knee amputees showed greater thigh acceleration on the affected side (22m/s2 ± SD 9 versus 13m/s2 ± SD6 for the unaffected side, p=0.02) whereas rotationplasty patients exhibited greater acceleration on the normal side (29m/s2 ± SD7 versus 15m/s2 ± SD5, p=0.0009). Amputees exerted stronger thigh forces (166N ± SD56 versus 105N ± SD47, p=0.005) on the operated side compared to the unaffected side, while KRP patients generated weaker thigh forces on the post-operative side (105N ± SD42 versus 208 ± SD62, p=0.02). MSTS scores were not statistically significant between the two groups.
Conclusions
Above-knee amputated limbs are stronger and more functionally normal than rotationplasty limbs. Advances in prosthetic design may eventually circumvent the need for this more complex procedure.
A new method for energizing multi-radiofrequency ion trap electrodes with adjustable amplitude and identical phase maintenance
Authors: Wang Qikun , Wang Zhao , Wang Xu 
Published: September 2023

Abstract
A helical resonator with a certain resonant frequency and a high-quality factor (Q-factor)[1] is critical for an ion trap system, which results in a larger trap depth, longer trap time, and lower RF noise. Here we propose a new method for energizing amplitude-adjustable multiple RF ion trap electrodes. By dividing the output of the helical resonator into multiple circuits and simultaneously energizing the ion trap multi-RF electrodes, each circuit is composed of capacitors connected in series, and the desired amplitude is applied to the ion trap RF electrodes using capacitive voltage dividing. In contrast, the capacitance of the multi-RF capacitors connected in series is determined by three constraints. Different voltages for each circuit are realized while keeping the phase consistent. To demonstrate our proposed method in experiments, we first determine that the theory is feasible through circuit simulations and then confirm the method’s validity by comparing the measured results with the analog simulations. Our method can be applied to the ion trap structure of multiplexed RF electrodes, which contributes to the realization of ion traps for multiplexed RF electrodes.
Statistical Inference on the Three Parameters Burr-XII Distribution Using the Runge-Kutta Method
Authors: Maswadah M. 
Published: September 2023

Abstract
In parameter estimation techniques, there are many methods for estimating the distribution parameters in life data analysis. However, most of them are less efficient than the Bayes method based on the informative prior. Thus, the main objective of this study is to present an optimal estimation method using the Runge-Kutta technique for estimating the three parameters of the Burr type-XII distribution. The Runge-Kutta estimates are compared with the Bayesian estimates based on the informative gamma and kernel priors via an extensive Monte Carlo simulation. The simulation results indicated that the Runge-Kutta method is highly favorable, which provides better estimates and outperforms the Bayes method based on the generalized progressive hybrid censoring scheme. Finally, two real datasets are presented to illustrate the efficiency of the proposed methods.
Enhancing Intrusion Detection Systems: A Comparative Study of Machine Learning Techniques for Cyber Security
Authors: Nabi Faisal 
Published: September 2023

Abstract
Our research aims to improve automated intrusion detection by developing a highly accurate classifier with minimal false alarms. The motivation behind our work is to tackle the challenges of high dimensionality in intrusion detection and enhance the classification performance of classifiers, ultimately leading to more accurate and efficient detection of intrusions. To achieve this, we conduct experiments using the NSL-KDD data set, a widely used benchmark in this domain. This data set comprises approximately 126,000 samples of normal and abnormal network traffic for training and 23,000 samples for testing. Initially, we employ the entire feature set to train classifiers, and the outcomes are promising. Among the classifiers tested, the J48 tree achieves the highest reported accuracy of 79.1 percent. To enhance classifier performance, we explore two projection approaches: Random Projection and PCA. Random Projection yields notable improvements, with the PART algorithm achieving the best-reported accuracy of 82.0%, outperforming the original feature set. Moreover, random projection proves to be more time-efficient than PCA across most classifiers. Our findings demonstrate the effectiveness of random projection in improving intrusion detection accuracy while reducing training time. This research contributes valuable insights to the cybersecurity field and fosters potential advancements in intrusion detection systems.
An examination of the relationship between volatility, liquidity and trading activity
Authors: Regaieg Boutheina , Hassini Nafissa 
Published: September 2023

Abstract
We investigate the influence of the firm value on the relationship between equity trading activity, market liquidity and return volatility at the portfolio level. For the different firm-value portfolio, we find that trading activity is negatively associated with liquidity but it is positively associated with volatility so higher trading activity leads to more volatile returns. For the very largest firm-value portfolio, the volatility-liquidity relationship is negative. However, this relationship is positive for other portfolios.
Optimal Consumption-Investment and CAPMs under a Quadratic Model based on Homothetic Robust Epstein--Zin Utility
Authors: Kusuda Koji , Kikuchi Kentaro , Batbold Bolorsuvd 
Published: September 2023

Abstract
This paper presents a theoretical analysis of the consumption-investment problem and CAPMs based on homothetic robust Epstein--Zin utility under a quadratic security market model in which interest rates, the market price of risk, the variances and covariances of asset returns, and inflation rates are stochastic. Robust investors first determine the ''conditional worst-case probability'' of minimizing utility for a given consumption and investment and then determine the optimal consumption and investment that maximizes utility under the conditional worst-case probability. The optimal consumption-investment decisions implicitly determine the worst-case probability. We clarify the theoretical structures of i) the budget constraint and market price of risk under the conditional worst-case probability; ii) the market price of risk under the worst-case probability; iii) the CAPMs; and iv) the CAPMs under the worst-case probability.
JEL classification C61, D81, G11
A new design of seat suspension using different models of negative stiffness structure
Authors: Yuan Huan , Li Hongwei , Lu Wei 
Published: September 2023

Three models of seat suspension using the negative stiffness structure including steel springs (SS), roller springs (RS), and tuned mass damper (TMD) are proposed and studied to improve the driver's seat ride comfort. Based on the dynamic models of the SS, RS, and TMD, their isolation efficiency and driver’s ride comfort are evaluated via two indexes of the root mean square displacement and acceleration of the seat (zws and aws) under two excitations of the random road surface and bumpy road surface. The results show that under the random road surface, the zws and aws with the seat's RS are reduced by 10.31 % and 20.32 % in comparison with the seat’s SS; whereas the zws and aws with the seat's TMD are smaller than that of the seat's RS by 19.15 % and 26.13 %; and the seat’s SS by 27.49 % and 41.15 %, respectively. Besides, the seat's displacement and acceleration responses with the seat’s TMD are also lower than that of both the SS and RS under the bumpy road surface. Therefore, the structure of the TMD should be designed and added to the seat suspension to enhance the driver’s seat ride comfort.
lmplementation of a national regulatory framework for drinking water safety plans in Uruguay
Authors: Vieira Jose M. P. , Rodríguez Sandra , Suarez Paula , Kramer Ricardo 
Published: September 2023

Abstract

The establishment of national strategic frameworks for systematic scaling-up of water safety plans (WSPs) implementation needs to overcome major constraints: lack of legislation and policies, and the need for appropriate monitoring tools. In 2018, the Uruguayan regulator for energy and water services promulgated a regulation intended to ensure an ambitious and pragmatic strategy that supports and promotes WSP implementation and auditing at a national scale. The goal is to have all drinking water supply systems with their WSP implemented by 2030. For this, a demanding schedule was recommended considering the size of the drinking water supplies: (i) large systems serving more than 2,000 inhabitants and (ii) small and very small systems serving fewer than 2,000 inhabitants. A mandatory verification through internal and external audits was also established. This work describes the legal and regulatory framework as well as the challenges and opportunities that open up for the generalization of WSP implementation in Uruguay. Despite the impact of COVID-19 on working conditions for water suppliers, as for the year 2022, WSPs have been successfully implemented in 94 water systems serving more than 2.4 million people. Results of successful implementation and auditing processes are presented and discussed covering methods and outcomes.