bluuebunny/crossref_metadata_2025_split huggingface dataset:
Increased oxidative stress caused by impaired mitophagy aggravated liver ischemia and reperfusion injury in diabetic mice
Authors: Zhijun Kong , Xudong Zhang , Baoqiang Wu , Chunfu Zhu , Qiang Yu , Yuan Gao , Xihu Qin 
Published: November 2022

AbstractAims/IntroductionEmerging evidence has suggested the detrimental role of oxidative stress in aggravating ischemia and reperfusion (IR) injury in diabetic livers. Interplay between oxidative stress and mitophagy has been shown. However, the role and mechanism of mitophagy in regulating oxidative stress and IR injury in diabetic livers remain unclear.Materials and MethodsWild‐type anddb/db(DB) mice were subjected to a partial warm liver IR model. Liver injury, oxidative stress, mitophagy and related molecular pathways were analyzed.ResultsHere, we found that increased liver IR injury was observed in DB mice, as evidenced by higher levels of serum alanine aminotransferase and serum aspartate, worsened liver architecture damage and more hepatocellular death. DB mice also showed increased mitochondrial oxidative stress. Mitochondrial reactive oxygen species scavenge alleviated liver IR injury in DB mice. Mechanistic analysis showed that 5′ adenosine monophosphate‐activated protein kinase‐mediated mitophagy was suppressed in DB mice post‐IR. Pharmacological activation of 5′ adenosine monophosphate‐activated protein kinase by its agonist effectively restored mitophagy activation, leading to decreased mitochondrial oxidative stress and attenuated liver IR injury in DB mice.ConclusionsOur findings showed that diabetes increased oxidative stress to exacerbate liver IR injury by impairing 5′ adenosine monophosphate‐activated protein kinase‐mediated mitophagy. Strategies targeting oxidative stress and mitophagy might provide a promising approach to ameliorate liver IR injury in diabetes patients.
Value of machine learning algorithms for predicting diabetes risk: A subset analysis from a real‐world retrospective cohort study
Authors: Mao Yaqian , Zhu Zheng , Pan Shuyao , Lin Wei , Liang Jixing , Huang Huibin , Li Liantao , Wen Junping , Chen Gang 
Published: November 2022

AbstractAims/IntroductionTo compare the application value of different machine learning (ML) algorithms for diabetes risk prediction.Materials and MethodsThis is a 3‐year retrospective cohort study with a total of 3,687 participants being included in the data analysis. Modeling variable screening and predictive model building were carried out using logistic regression (LR) analysis and 10‐fold cross‐validation, respectively. In total, six different ML algorithms, including random forests, light gradient boosting machine, extreme gradient boosting, adaptive boosting (AdaBoost), multi‐layer perceptrons and gaussian naive bayes were used for model construction. Model performance was mainly evaluated by the area under the receiver operating characteristic curve. The best performing ML model was selected for comparison with the traditional LR model and visualized using Shapley additive explanations.ResultsA total of eight risk factors most associated with the development of diabetes were identified by univariate and multivariate LR analysis, and they were visualized in the form of a nomogram. Among the six different ML models, the random forests model had the best predictive performance. After 10‐fold cross‐validation, its optimal model has an area under the receiver operating characteristic value of 0.855 (95% confidence interval [CI] 0.823–0.886) in the training set and 0.835 (95% CI 0.779–0.892) in the test set. In the traditional LR model, its area under the receiver operating characteristic value is 0.840 (95% CI 0.814–0.866) in the training set and 0.834 (95% CI 0.785–0.884) in the test set.ConclusionsIn the real‐world epidemiological research, the combination of traditional variable screening and ML algorithm to construct a diabetes risk prediction model has satisfactory clinical application value.
Substitution of cocoa powder with hazelnut skin powder in cocoa hazelnut spreads
Authors: Şahin Sümeyye , Özata Amine Beyza 
Published: November 2022

AbstractIn this study, the potential of hazelnut skin powder (HSP) as a cocoa powder (CP) substitute in the production of cocoa hazelnut spreads was evaluated. CP was replaced with HSP at the ratio of 15%, 30%, and 45% by weight in novel formulations. Free fatty acid (FFA), peroxide value (PV), fatty acid composition, instrumental color and textural properties, sensory attributes, total phenolic content (TPC), antioxidant capacity (AC), and microbial load of the final products were investigated after 30, 60, 90, 180, and 270 days of storage. FFA and PV of cocoa hazelnut spreads significantly increased during storage (p < .05). Palmitic, oleic, and linoleic acid were determined as predominant fatty acids in the new cocoa hazelnut spreads. The cocoa hazelnut spreads with HSP were generally preferred by panelists, and the highest overall acceptability was observed in the cocoa hazelnut spread with 15% HSP. In addition, the substitution of CP with HSP significantly increased TPC, while it did not affect AC.Practical applicationsSubstitution of the cocoa powder with hazelnut skin powder enhanced the textural and sensory properties of the cocoa hazelnut spreads. In addition, a healthier product containing more phenolics can be produced by partially replacing cocoa powder with hazelnut skin powder. The use of hazelnut skin powder as cocoa powder substitute could provide cost reduction in the production of cocoa hazelnut spread and contribute to zero waste in the industry.
Changes in physico‐chemical attributes and reaction kinetics of Palmyra (Borassus flabellifer) sap stored under ambient and refrigerated temperature during fermentation
Authors: Sarma Chayanika , Kalakandan Suresh Kumar , Mummaleti Gopinath , Thamburaj Suman 
Published: November 2022

AbstractThe change in physicochemical properties of palmyra sap and fermentation kinetics on storage at different storage conditions need to be studied in order to understand the stability of sap and to develop an efficient technique for improving the shelf‐life of palmyra sap. The objective of this current study was to explore the changes in physico‐chemical properties of palmyra sap during ambient (30 ± 2°C) and refrigerated (7 ± 1°C) storage. The palmyra sap collected was bottled and stored, and changes in physicochemical properties were studied every 10 h. The sucrose, glucose, and fructose content of fresh sap was observed to be 14.22 ± 0.14, 1.41 ± 0.01, and 0.52 ± 0.02 (g/100 ml), which were degraded on storage. The alcohol content increased up to 6.24% after 10 h of storage in ambient conditions. The sucrose degradation in the palmyra sap followed first‐order equation in the sap stored under ambient conditions. There are no significant changes in the properties of palmyra sap stored under refrigerated conditions.Novelty impact statementThis study is a first report on physico‐chemical changes in naturally obtained palmyra (Borassus flabellifer) sap. Fermentation kinetics were studied at ambient and refrigerated temperature using zero‐, first‐, and second‐order models that helps in predicting physicochemical changes and estimating the shelf‐life of the palmyra sap. Physicochemical changes followed first‐ and second‐order reaction model which helped in predicting the shelf life of palmyra sap. The alcohol content was found to be absent in palmyra sap under refrigerated condition.
Incidence of skin malignancies in patients with vitiligo or psoriasis who received narrowband ultraviolet B phototherapy (308 nm/311 nm): A retrospective review of 3730 patients
Authors: Chia Brian Keng Yang , Yew Yik Weng , Zhao Xiahong , Chong Wei‐Sheng , Thng Tien Guan Steven 
Published: November 2022

AbstractBackgroundPrevious studies regarding the risk of skin malignancy with NBUVB have been performed in Caucasian patients, but few studies have been conducted in Asians.AimThe aim of the study was to determine the risk of skin cancer in Asian patients with psoriasis and vitiligo receiving NBUVB phototherapy.MethodsWe performed a 9‐year retrospective study including all patients with psoriasis and vitiligo receiving NBUVB (either 311 nm wavelength through cabin phototherapy or 308 nm through excimer lamp phototherapy) at the National Skin Centre. We matched the identification numbers of patients to the National Registry of Diseases Office database and collected data on all skin cancers diagnosed.ResultsA total of 3730 patients were included. During the course of the study, 12 cases of skin cancer were diagnosed, of which 10 were basal cell carcinomas, and 2 were squamous cell carcinomas. No cases of melanoma were detected in the study. The age‐standardized incidence of skin cancer in psoriasis and vitiligo patients who received phototherapy was 47.5 and 26.5, respectively, which is higher than the incidence of skin cancers in the general population. Risk of skin malignancy was positively correlated with the cumulative (p = .008) and maximum dose of phototherapy (p = .011) as well as previous systemic treatments (p = .006).LimitationsLimitations include a relatively short follow‐up period as well as the lack of quantification of solar exposure.ConclusionsNBUVB phototherapy in Asian skin increases the risk of skin malignancy. The risk of skin malignancy is higher with psoriasis patients, greater cumulative and maximal dose of phototherapy as well as the use of systemic therapy. Despite the increased risk, the absolute number of skin malignancies remains low, especially for vitiligo patients, with no cases of melanoma diagnosed—a reassuring finding that phototherapy remains a safe alternative in the treatment of psoriasis and vitiligo.
COVID-19 Clinical Footprint to Infer About Mortality
Authors: Rodríguez Carlos E. , Mena Ramsés H. 
Published: November 2022

Abstract
Information on 4.1 million patients identified as COVID-19 positive in Mexico is used to understand the relationship between comorbidities, symptoms, hospitalisations and deaths due to the COVID-19 disease. Using the presence or absence of these variables a clinical footprint for each patient is created. The risk, expected mortality and the prediction of death outcomes, among other relevant quantities, are obtained and analysed by means of a multivariate Bernoulli distribution. The proposal considers all possible footprint combinations resulting in a robust model suitable for Bayesian inference. The analysis is carried out considering the information on the monthly COVID-19 cases, from March 2020 to the first days of January 2022. This allows one to appreciate the evolution of the mortality risk over time and the effect the strategies of the health authorities have had on it. Supporting information for this article, containing code and the dataset used for the analysis, is available online.
Asymptotic approximation of a highly oscillatory integral with application to the canonical catastrophe integrals
Authors: Ferreira Chelo , López José L. , Pérez Sinusía Ester 
Published: November 2022

AbstractWe consider the highly oscillatory integral for large positive values of w, , K and p positive integers with , and an entire function. The standard saddle point method is complicated and we use here a simplified version of this method introduced by López et al. We derive an asymptotic approximation of this integral when for general values of K and p in terms of elementary functions, and determine the Stokes lines. For , the asymptotic behavior of this integral may be classified in four different regions according to the even/odd character of the couple of parameters K and p; the special case requires a separate analysis. As an important application, we consider the family of canonical catastrophe integrals for large values of one of its variables, say , and bounded values of the remaining ones. This family of integrals may be written in the form for appropriate values of the parameters w, θ and the function . Then, we derive an asymptotic approximation of the family of canonical catastrophe integrals for large . The approximations are accompanied by several numerical experiments. The asymptotic formulas presented here fill up a gap in the NIST Handbook of Mathematical Functions by Olver et al.
Student Negotiation of Collaborative Dialogues: The Roles and Resources Used in Unsupervised Conversations
Authors: Groepper Emily 
Published: November 2022

AbstractResponding to Donato and Brooks's (2004) call for undergraduate students to have more opportunities to engage in discourse at the advanced proficiency level, collaborative dialogues provide students with a situation conducive to language production and learning (Swain, 1997). As most of the research on collaborative dialogues has focused on the accuracy of language in a classroom environment, this article explores the various ways learners work together collaboratively to make meaning while discussing course content in the target language in dialogues taking place outside of class. Four student dyads with mixed proficiency levels completed weekly collaborative dialogues in an advanced undergraduate German literature course, and the dialogues were analyzed for patterns in role‐taking and resource usage with an emphasis on how the students negotiated the task to complete it and make meaning. The students stayed on task during the dialogues and assumed the collaborative, expert, novice, dominant, and passive roles described by Storch (2002) during their discussion. They also relied almost solely on each other as linguistic resources.
“Tesla in Grünheide”: Growing Intercultural Competence Through Role‐Play Simulation
Authors: Joo Hyoun‐A , Tuschling Lina 
Published: November 2022

AbstractThe development of intercultural communicative competence (ICC) becomes increasingly important in the world language curriculum and a crucial goal to prepare students for real‐life communicative situations outside of the classroom. This article discusses how a simulation exercise based on the contentious construction of the Tesla Gigafactory in Grünheide, Germany, facilitated the growth of students' ability to take perspectives other than their own – a crucial step toward ICC. Using the controversies about the Tesla Gigafactory as a real‐world case study, students participated in a role‐play simulation, set up as a town hall meeting, where they had to develop arguments whether Tesla should be given the official construction permit or not. This project‐based and student‐led exercise was designed to develop critical awareness of the cultural intricacy of the Tesla case by considering authentic dilemmas and conflicting perspectives. The activity was implemented in a virtual study abroad, advanced‐level German course. Comparing responses from a student feedback survey with Byram's ICC model (2021) suggests that the exercise helped students increase their factual knowledge, skills of interpreting, relating, discovering, and interacting, and develop differentiated understanding of other perspectives – important 21st‐century ICC skills for a global life and work environment.
A critique of Malpass's argument against Supervaluationism
Authors: De Florio Ciro , Frigerio Aldo 
Published: November 2022

AbstractSupervaluationism is one of the most discussed approaches to the semantics of future tense sentences in a branching time. In this paper, we consider the criticism advanced by Malpass against Supervaluationism. This criticism relies on the fact that supervaluationists must accept as supertrue disjunctions whose disjuncts are not only supertrue—which supervaluationists are ready to acknowledge—but also not satisfiable. In order to show this, Malpass proposes a formula, , which shows the existence of a satisfiable disjunction with unsatisfiable disjuncts in supervaluationist models. In reply, we show that formula cannot be expressed within a model (whether Ockhamist or supervaluationist) because it quantifies on models. It can be correctly characterised only within a meta‐model that has the resources to quantify on various models. However, once that is done, is, for the advocates of Supervaluationism, no more demanding than other disjunctions because it just generalises at the meta‐theoretical level what supervaluationists already acknowledge at the theoretical level.
Rule-Based Time-Optimal Engine-Start Coordination Control With a Predesigned Vehicle Acceleration Trajectory in P2 Hybrid Electric Vehicles
Authors: Lu Ziwang , Tian Guangyu , Onori Simona 
Published: November 2022

Abstract
Removing the integrated starter generator (ISG) in P2 hybrid electric vehicles (HEVs) reduces the overall cost of the powertrain, yet it comes with an additional control complexity of the engine-start process. An appropriate coordination control strategy between the internal combustion engine (ICE), drive motor, and clutch is necessary to reduce the time for the engine-start while constraining the vehicle jerk. A time-optimal coordination control strategy with a predesigned vehicle acceleration trajectory is proposed from results of nonlinear model predictive control (NMPC), which can reduce the time for the engine-start process and obtain a small vehicle jerk. A dynamic model for the engine-start process is first built. In this model, a cylinder-by-cylinder engine model (CCEM) is derived to describe the ICE dynamics. A Karnopp and Stribeck combined wet clutch model is proposed to handle effects of speed difference on the torque, and calculation problem of frequent switches when crossing zero speed point. Subsequently, the optimal control problem is formulated with selected states and solved with NMPC. Finally, a rule-based control strategy is extracted from results of NMPC. Simulation results show that the engine-start process can finish within 260 ms, 13.3% less than the previous study, with a predesigned vehicle acceleration to ensure the vehicle jerk within 10 m/s3 and the peak to peak vehicle acceleration within 0.2 m/s2 in the case study under investigation.
Comparison of a Scaled Cadaver-Based Musculoskeletal Model With a Clinical Upper Extremity Model
Authors: Nagaraja Vikranth H. , Bergmann Jeroen H. M. , Andersen Michael S. , Thompson Mark S. 
Published: November 2022

Abstract
Reliably and accurately estimating joint/segmental kinematics from optical motion capture data has remained challenging. Studies objectively characterizing human movement patterns have typically involved inverse kinematics and inverse dynamics techniques. Subsequent research has included scaled cadaver-based musculoskeletal (MSK) modeling for noninvasively estimating joint and muscle loads. As one of the ways to enhance confidence in the validity of MSK model predictions, the kinematics from the preceding step that drives such a model needs to be checked for agreement or compared with established/widely used models. This study rigorously compares the upper extremity (UE) joint kinematics calculated by the Dutch Shoulder Model implemented in the AnyBody Managed Model Repository (involving multibody kinematics optimization (MKO)) with those estimated by the Vicon Plug-in Gait model (involving single-body kinematics optimization (SKO)). Ten subjects performed three trials of (different types of) reaching tasks in a three-dimensional marker-based optical motion capture laboratory setting. Joint angles, processed marker trajectories, and reconstruction residuals corresponding to both models were compared. Scatter plots and Bland–Altman plots were used to assess the agreement between the two model outputs. Results showed the largest differences between the two models for shoulder, followed by elbow and wrist, with all root-mean-squared differences less than 10 deg (although this limit might be unacceptable for clinical use). Strong-to-excellent Spearman's rank correlation coefficients were found between the two model outputs. The Bland–Altman plots showed a good agreement between most of the outputs. In conclusion, results indicate that these two models with different kinematic algorithms broadly agree with each other, albeit with few key differences.
Multi-Objective Optimal Regulation of Glucose Concentration in Type I Diabetes Mellitus
Authors: Shaker Raya Abu , Sardahi Yousef , Alshorman Ahmad 
Published: November 2022

Abstract
Type I, or insulin-dependent diabetes mellitus, is a chronic disease in which insulin is not adequately produced by the pancreatic β-cells, which leads to a high glucose concentration. In practice, external insulin delivery is the only method to deal with this disease. To this end, a multi-objective optimal control for insulin delivery is introduced in this paper. Three conflicting objectives, including minimizing the risk of hypoglycemia and hyperglycemia, and reducing the amount of injected insulin, are considered. These objectives are minimized simultaneously while tuning the closed-loop system parameters that include the design details of the linear-quadratic regulator (LQR) and estimator speed of convergence. The lower and upper bounds of the LQR setup parameters are determined by Bryson’s rule taking into account the nominal glucose range (70−160  mg/dL) and maximum and minimum pump infusion rates (0.0024−15 mU/min). The lower and upper bounds of the estimator convergence speed are chosen such that the estimator is faster than the fastest mode of the closed-loop system. For computer simulations, Bergman’s minimal model, which is one of the commonly used models, is employed to simulate glucose-insulin dynamics in Type-I diabetic patients. The optimization problem is solved by the nondominated sorting genetic algorithm (NSGA-II), one of the widely used algorithms in solving multi-objective optimization problems (MOPs). The optimal solutions in terms of the Pareto set and its image, the Pareto front, are obtained and analyzed. The results show that the MOP solution introduces many optimal options from which the decision-maker can choose to implement. Furthermore, under high initial glucose levels, parametric variations of Bergman’s model, and external disturbance, the optimal control performance are tested to show that the system can bring glucose levels quickly to the desired value regardless of high initial glucose concentrations, can efficiently work for different patients, and is robust against irregular snacks or meals.
Particles Transportation and Deposition Behavior During Horizontal Wellbore Exploitation
Authors: Yang Liu , Li Yu , Wang Deguo , Li Dongyang 
Published: November 2022

Abstract
Particles deposition and plug-in wellbore cause lots of damage and efficiency reduction during oil and gas exploitation. Transportation has been a focus for safety and production improvement. The annular flow field and particles transport behavior have been investigated using computational fluid dynamics with an renormalization group k–ɛ method. Effects of particles volume concentration, washing fluid concentration with power-law shearing, annular eccentricity, flow rate, and rotation speed have been researched to get the mechanism of particles accumulation and transport behavior. The results show that an increase in eccentricity causes velocity reduction of the annular narrow gap area, particles easily deposit, accumulate, and are hard to transport; increasing flow rate and fluid concentration apparently improve particles transportation and reduce deposition, pressure loss increases; inlet particles volume concentration increases deposition starting position and deposition length, the inner pipe rotation facilitates particles’ second suspension.