bluuebunny/crossref_metadata_2025_split huggingface dataset:
Similarities in steering control between cars and motorcycles: application to a low-complexity riding simulator
Authors: Bartolozzi Mirco , Berzi Lorenzo , Meli Enrico , Savino Giovanni 
Published: October 2022

AbstractMotorcycle simulators are employed for rider training, studying human–machine interaction, and developing assistance systems. However, existing simulators are either too simple and, therefore, unsuitable or significantly complex, with higher hardware costs and familiarisation times. This study aimed to use a tuned single-track car model as the basis of a motorcycle simulator, leading to considerable software simplification while preserving its fidelity. In particular, the approach defined a conversion between motorcycle steering torque and car steering angle. It modified the parameters of the latter to reproduce the response of various motorcycle models in quasi-static and transient conditions for different speeds and radii of curvature. A robust manoeuvrability index was chosen. For the car, it was possible to calculate it from its parameters analytically. Next, the car yaw inertia was tuned to obtain a motorcycle-like steering response. Finally, the calibrated car model was implemented into a low-complexity motorcycle simulator for objective validation. It was verified that an understeering single-track model with high yaw inertia has amplitude and phase responses analogous to a motorcycle. The experimental results of the simulator test confirmed these findings for a diverse set of manoeuvres, validating the method. This straightforward approach allows the development of low-complexity simulators with good steering fidelity, using an objective procedure to reproduce the behaviour of a chosen motorcycle class. In addition, the low computational cost of the model makes it a potential candidate for use in assistance systems.
Screening saikosaponin d (SSd)-producing endophytic fungi from Bupleurum scorzonerifolium Willd
Authors: Cheng Yupeng , Liu Guangjie , Li Zhongmeng , Zhou Yongqiang , Gao Ning 
Published: October 2022

AbstractSaikosaponin d (SSd) is an important bioactive compound of traditional Chinese medicinal plant Bupleurum scorzonerifolium Willd. and exhibits many effects, such as anti-tumor, anti-inflammation and immunomodulatory. Since endophytic fungi possess the natural capacity to produce the similar secondary metabolite to that of their host plants, they are promising as alternative sources of plant bioactive natural products. In this study, in order to search for SSd-producing strains, endophytes were isolated from B. scorzonerifolium and were authenticated by the ITS sequence and the translation elongation factor-1alpha gene (TEF-1α) sequence analysis. The profile of metabolites present in the crude exacts was carried out by ultra performance liquid chromatography time-of-flight mass spectrometry (UPLC/Q-TOF-MS) analysis. The results showed that two strains, CHS2 and CHS3 from B. scorzonerifolium could produce SSd by UPLC/Q-TOF-MS analysis, and the amount of SSd produced by strain CHS2 and CHS3 were about 2.17 and 2.40 µg/mL, respectively. CHS2 and CHS3 showed a close phylogenetic relationship to Fusarium oxysporum and Fusarium acuminatum, respectively. According to our concern, no endophytic fungi capable of producing SSd from B. scorzonerifolium have been found before. Our clear intention was to isolate and identify these endophytic fungi that produce important active secondary metabolites, and then study the strains that produce this compound on a large scale through fermentation or even genetic study, to provide a feasible and more convenient way for the production of SSd.
Dehydrozingerone promotes healing of diabetic foot ulcers: a molecular insight
Authors: Begum Farmiza , Manandhar Suman , Kumar Gautam , Keni Raghuvir , Sankhe Runali , Gurram Prasada Chowdari , Beegum Fathima , Teja Meka Sai , Nandakumar Krishnadas , Shenoy Rekha R. 
Published: October 2022

Abstract
Introduction
One of the most common problems of diabetes are diabetic foot ulcers (DFUs). According to National Institute for Health, initial management of DFUs can decrease the complication of limb amputations and can improve the patient’s quality of life. DFU treatment can be optimized with the help of multidisciplinary approach. Based on many studies, control of glucose levels in blood, antioxidant activity, reduction in cytokine levels, re-epithelialization, collagen formation, migration of fibroblasts are major phases involved in managing DFU. Dehydrozingerone (DHZ), has been known for its anti-inflammatory, antioxidant and wound healing properties.

Methodology
Three months high-fat diet and low dose of streptozotocin-induced type-II diabetic foot ulcer model was used to evaluate the effectiveness of dehydrozingerone. DHZ was given orally to rats for 15 days post wounding. TNF-α, IL-1β and antioxidant parameters like lipid peroxidation, glutathione reductase were estimated. Immunoblotting was done to investigate the effect of DHZ on the expression of ERK, JNK, HSP-27, P38, SIRT-1, NFκB, SMA, VEGF and MMP-9 in skin tissue. Histopathology was performed for analyzing DHZ effect on migration of fibroblasts, formation of epithelium, granulation tissue formation, angiogenesis and collagen formation.

Results
DHZ decreased the levels of malondialdehyde, TNF-α, IL-1β and increased glutathione levels in wound tissue. Western blotting results suggested that DHZ activated ERK1/2/JNK/p38 signaling, increased expression of HSP-27, SIRT-1, VEGF, SMA thus facilitating the migration and proliferation of fibroblasts, angiogenesis and decreased inflammation. Masson Trichrome & histopathology showed an increase in collagen, epithelial and granulation tissue formation.

Conclusion
DHZ significantly accelerates the healing of diabetic foot ulcers in high fat diet fed plus low dose streptozotocin induced type-II diabetic Wistar rats.

Graphical abstract
CD44 and CD221 directed magnetic cubosomes for the targeted delivery of helenalin to rhabdomyosarcoma cells
Authors: Mun Hakmin , Chaban Yuriy , Tabish Tanveer A. , Thorat Nanasaheb , Cowieson Nathan , Owen C. David , Townley Helen E. 
Published: October 2022

AbstractConfining chemotherapy to tumour sites by means of active targeting nanoparticles (NPs) may increase the treatment effectuality while reducing potential side effects. Cubosomes are one of the next-generation drug delivery nanocarriers by virtue of their biocompatibility and bioadhesion, sizeable payload encapsulation and high thermostability. Herein, an active tumour targeting system towards rhabdomyosarcoma (RMS) cells was evaluated. Cubosomes were loaded with helenalin (a secondary metabolite from Arnica plants), which we have previously shown to induce apoptosis in RMS cells. The functionalization of the cubosomes was accomplished to enable binding to membrane receptors and translocation under a magnetic field. RMS cells overexpress CD44 and CD221 on their membrane surface and, therefore, hyaluronic acid (HA, a ligand for CD44) and antibodies (Abs) against CD221 were coupled to cubosomes via electrostatic attraction and the thiol-Michael reaction, respectively. Magnetization of the cubic phase NPs was achieved by embedding superparamagnetic iron oxide NPs (SPIONPs) into the cubic matrix. Single-function and multi-function cubosomes had Im3m cubic phase structures with well-organized lattice patterns. Conjugation with 2% HA or anti-CD221 half Abs and/or 1% SPIONPs showed significantly higher uptake into RMS cells compared to unfunctionalized cubosomes. CD44 and CD221 directed magnetic (triple-function) cubosomes were capable of internalizing into RMS cells in an energy-independent mechanism. Helenalin-laden triple functionalized cubosomes showed limited impact on the viability of control fibroblast cells, while they induced a high degree cytotoxicity against RMS cells. Profound tumour cell death was observed in both two-dimensional (2D) culture and three-dimensional (3D) tumour spheroids.
Some considerations on the role of joint spacing in rock slope stability analyses using a 3D discrete element approach
Authors: Pérez-Rey Ignacio , Muñiz-Menéndez Mauro , Moreno-Robles Javier 
Published: October 2022

AbstractStability assessment of potential wedge failures in rock slopes is usually carried out based on stereographic projection techniques and limit equilibrium analyses. Nevertheless, this methodology presents several limitations (i.e., lack of information on joint mechanical properties, oversimplification of the structure, etc.) that could lead to poorly accurate conclusions. In line with this idea, the main objective of this work is to evaluate the effect of joint spacing in the estimation of the factor of safety of rock slopes affected by potential wedge failures. For this purpose, a 3D numerical distinct element code (3DEC) was selected to carry out a substantial number of simulations in which the factor of safety of two types of slopes, affected by different discontinuity sets, was studied by using the shear strength reduction (SSR) method. Different values of joint spacing, cohesion, and friction angles were considered, combined with two angles of the slope face under study. A discrete fracture network (DFN) model was also implemented, with the aim of benchmarking results with those obtained from the original models. The joint spacing has been found to relevantly affect the values of the factor of safety of the slope, which showed variations of up to 40% in comparison with those obtained from limit equilibrium methods. This work provides an insight to a more realistic interpretation of rock slope analyses against wedge failures, particularly to better estimations of the factor of safety.
A descriptive human visual cognitive strategy using graph neural network for facial expression recognition
Authors: Liu Shuai , Huang Shichen , Fu Weina , Lin Jerry Chun-Wei 
Published: October 2022

AbstractIn the period of rapid development on the new information technologies, computer vision has become the most common application of artificial intelligence, which is represented by deep learning in the current society. As the most direct and effective application of computer vision, facial expression recognition (FER) has become a hot topic and used in many studies and domains. However, the existing FER methods focus on deep learning to generate increasingly complex attention structures, so they are unable to consider the connotative relationship between different parts of facial expressions. Moreover, the human expression recognition method based on complex deep learning network has serious interpretability issues. Therefore, in this paper, a novel Graph Neural Network (GNN) model is proposed to consider the systematic process of FER in human visual perception. Firstly, a region division mechanism is proposed, which divides the face region into six parts to unify the selection of key facial features. On this basis, in order to better consider the connotative relationship between different parts of facial expression, a human visual cognition strategy is proposed, which uses the divided six regions to learn facial expression features, and evenly selects the key features with high reliability as graph nodes. In combination with the human regional cooperative recognition process, the connotative relationship (such as relative position and similar structure) between graph nodes is extracted, so as to construct the GNN model. Finally, the effect of FER is obtained by the modeled GNN model. The experimental results compared with other related algorithms show that the model not only has stronger characterization and generalization ability, but also has better robustness compared with state-of-the-art methods.
Road pricing and spatial distribution of traffic flow in radial-arc network
Authors: Miyagawa Masashi 
Published: October 2022

AbstractThis paper discusses the effect of road pricing on the spatial distribution of traffic flow. The traffic flow density is derived for a circular city with a radial-arc network. The traffic flow density describes the amount of traffic as a function of position and allows us to identify the location of potential congestion areas. The analytical expression for the traffic flow density demonstrates how the size of the toll area and the toll level affect the spatial distribution of traffic flow. As the size of the toll area increases, the decrease in traffic flow inside the toll area becomes smaller. As the toll level increases, the increase in traffic flow at the boundary of the toll area becomes greater. The effect of the travel cost on the spatial distribution of traffic flow is also examined. These findings can be used to determine the size of the toll area and the toll level required to achieve a certain level of traffic congestion.
Deep Neural Network Solution for Finite State Mean Field Game with Error Estimation
Authors: Luo Jialiang , Zheng Harry 
Published: October 2022

AbstractWe discuss the numerical solution to a class of continuous time finite state mean field games. We apply the deep neural network (DNN) approach to solving the fully coupled forward and backward ordinary differential equation system that characterizes the equilibrium value function and probability measure of the finite state mean field game. We prove that the error between the true solution and the approximate solution is linear to the square root of DNN loss function. We give an example of applying the DNN method to solve the optimal market making problem with terminal rank-based trading volume reward.
Case report. Forse macrohematurie uit urostoma: een potentieel levensbedreigende situatie!
Authors: Tilli Sander F. , Lock Tycho M. T. W. , Dik Pieter , de Jongh Rik 
Published: October 2022

SamenvattingDe arterio-ureterale fistel (AUF) is een zeldzame aandoening met een relatief hoge mortaliteit, die meestal voorkomt na uitgebreide pelviene oncologische chirurgie in combinatie met bestraling en chronische ureterale stenting. Jaarlijks worden in Nederland ongeveer vier AUF’s gediagnosticeerd, mogelijk ligt de frequentie zelfs hoger. De pathofysiologie van een AUF berust hoofdzakelijk op chronische inflammatie, fibrose, slechte vascularisatie en uiteindelijk druknecrose. Lokalisatie van een AUF is voornamelijk ter hoogte van de overkruising van de ureter met de arteria iliaca communis. AUF presenteert zich vaak in een acute setting met massaal bloedverlies. Een angiografie is het meest sensitieve diagnosticum en de behandeling van voorkeur betreft een endovasculaire interventie.
Phenylacetylglutamine as a novel biomarker of type 2 diabetes with distal symmetric polyneuropathy by metabolomics
Authors: Xu J. , Cai M. , Wang Z. , Chen Q. , Han X. , Tian J. , Jin S. , Yan Z. , Li Y. , Lu B. , Lu H. 
Published: October 2022

Abstract
Purpose
Type 2 diabetes mellitus (T2DM) with distal symmetric polyneuropathy (DSPN) is a disease involving the nervous system caused by metabolic disorder, while the metabolic spectrum and key metabolites remain poorly defined.

Methods
Plasma samples of 30 healthy controls, 30 T2DM patients, and 60 DSPN patients were subjected to nontargeted metabolomics. Potential biomarkers of DSPN were screened based on univariate and multivariate statistical analyses, ROC curve analysis, and logistic regression. Finally, another 22 patients with T2DM who developed DSPN after follow-up were selected for validation of the new biomarker based on target metabolomics.

Results
Compared with the control group and the T2DM group, 6 metabolites showed differences in the DSPN group (P < 0.05; FDR < 0.1; VIP > 1) and a rising step trend was observed. Among them, phenylacetylglutamine (PAG) and sorbitol displayed an excellent discriminatory ability and associated with disease severity. The verification results demonstrated that when T2DM progressed to DSPN, the phenylacetylglutamine content increased significantly (P = 0.004).

Conclusion
The discovered and verified endogenous metabolite PAG may be a novel potential biomarker of DSPN and involved in the disease pathogenesis.
Relationship between hyponatremia at hospital admission and cardiopulmonary profile at follow-up in patients with SARS-CoV-2 (COVID-19) infection
Authors: Malandrino D. , Berni A. , Fibbi B. , Borellini B. , Cozzi D. , Norello D. , Fattirolli F. , Lavorini F. , Olivotto I. , Fumagalli C. , Zocchi C. , Tassetti L. , Gozzi L. , Marchionni N. , Maggi M. , Peri A. ,   the AOU Careggi COVID-19 Follow-up Study Group, Spinicci Michele , Zammarchi Lorenzo , Gori Leonardo , Bernacchi Guja , Ciambellotti Lorenzo , Vellere Iacopo , Vannini Matteo , Montali Sara , Tonarelli Francesco , Camartini Viola , Turrin Giada , Testa Giuseppe Dario , Virciglio Simona , Gardellini Enrico , Corsi Carolina , Tofalos Sofia Espinoza , Marcucci Rossella , Rasero Laura , Giovannoni Lorenzo , Livi Luca , Silverii Maria Vittoria 
Published: October 2022

Abstract
Purpose
Hyponatremia occurs in about 30% of patients with pneumonia, including those with SARS-CoV-2 (COVID-19) infection. Hyponatremia predicts a worse outcome in several pathologic conditions and in COVID-19 has been associated with a higher risk of non-invasive ventilation, ICU transfer and death. The main objective of this study was to determine whether early hyponatremia is also a predictor of long-term sequelae at follow-up.

Methods
In this observational study, we collected 6-month follow-up data from 189 laboratory-confirmed COVID-19 patients previously admitted to a University Hospital. About 25% of the patients (n = 47) had hyponatremia at the time of hospital admission.

Results
Serum [Na+] was significantly increased in the whole group of 189 patients at 6 months, compared to the value at hospital admission (141.4 ± 2.2 vs 137 ± 3.5 mEq/L, p < 0.001). In addition, IL-6 levels decreased and the PaO2/FiO2 increased. Accordingly, pulmonary involvement, evaluated at the chest X-ray by the RALE score, decreased. However, in patients with hyponatremia at hospital admission, higher levels of LDH, fibrinogen, troponin T and NT-ProBNP were detected at follow-up, compared to patients with normonatremia at admission. In addition, hyponatremia at admission was associated with worse echocardiography parameters related to right ventricular function, together with a higher RALE score.

Conclusion
These results suggest that early hyponatremia in COVID-19 patients is associated with the presence of laboratory and imaging parameters indicating a greater pulmonary and right-sided heart involvement at follow-up.
Evaluation of the Bond Stress Transfer Mechanism in CFSTs
Authors: Somma Giuliana , Vit Michele 
Published: October 2022

AbstractThis paper studies the non-linear distribution of bond–slip behavior in the steel concrete interface of a Concrete Filled Steel Tube (CFST). Specifically, it concerns the regions of geometric discontinuity occurring in composite beams of CFST column-frame connection points. The study was conducted through an analytical model that represented the bond stress transfer mechanism within these areas. The resulting deductions were drawn up on the basis of the elasticity theory and the non-linear bond–slip relationship between the steel jacket and the confined concrete. This paper highlights how the model proposed here was able to obtain, not only the closed-form analytical expression of the transferring length involved in the bond stress transfer mechanism in CFSTs but also the expressions of concrete and steel jacket stresses and strains. In addition, the procedure also obtained the bond stress and slip trend in the above-mentioned length for rectangular and circular concrete filled steel tubes. The use of this model also resulted in an analytical expression for the calculation of the ultimate load in CFSTs. In this paper, the ultimate load predictions were compared with the experimental results obtained from 97 tests carried out on circular concrete filled tubes (CCFTs) and 35 tests on rectangular concrete filled tubes (RCFTs). The predictions drawn up with this model have been found to be the most accurate and uniform in comparison with those obtained from models proposed by other authors and Eurocode. With reference to the experimental-to-analytical load value ratio, the AVG and COV values obtained from the model proposed here are 0.86 and 0.42, and 1.06 and 0.57 for CCFT and RCFT analyses, respectively.
Fundamentalist formations in Germany? ultramontanist catholicism and national socialism
Authors: Schlamelcher Jens 
Published: October 2022

AbstractCentral Europe is often seen as the “exceptional case” in the sociology of religion with a high degree of secularization, traditional religions in a process of decline, and fundamentalist movements small in numbers. However, this may not have always been the case. This article elaborates the analytical advantages to conceive late 19th century Catholicism and early 20th century National Socialism as two distinctive fundamentalist formations in Germany. Seen in this light, in between 1850 and 1945, fundamentalist movements were able to attract large strata of the population in Germany. This article includes four parts. First, I outline what I mean by the term “fundamentalism”. Second, I will describe 19th century German Catholicism, and thirdly, early 20th century National Socialism as a fundamentalist movement. In the conclusion I will discuss if their labelling as fundamentalist formations may be justified.
Assortment planning and pricing for configurable product under sequential choice process
Authors: Wang Yana , Chen Zhen-Song , Wang Xian-Jia 
Published: October 2022

AbstractThe current paper considers a retailer selling a vertically differentiated configurable product (e.g., a mobile phone), which is a combination of a required component (e.g., CPU) and an optional component (e.g., headphone). Each component consists of several quality-differentiated variants from which customers can choose. Customers differ in their valuation for quality, and each customer independently chooses the variant that maximizes his utility. First, the scenario where a customer’s purchase decision depends on the prices and assortments of both the required and optional components is examined. The results indicate that the assortment and price optimization problem for configurable products can be separated into each component category’s assortment and price decisions. Furthermore, the optimal assortment of each component category does not depend on the distribution of customer valuations. It is comprised of the variants that are on the lowest convex envelope curve of the quality-cost graph of that category. An efficient algorithm is proposed to identify the retailer’s optimal decisions. Then, we examine the case where a customer evaluates an optional variant only if he decides to purchase a required variant. The results suggest that: (i) there exist some relationships between the optimal decisions in the base choice model and that in the sequential choice model; (ii) overlooking the sequential choice behavior may result in broader assortment, suboptimal prices, and profit loss.