bluuebunny/crossref_metadata_2025 huggingface dataset:
Neoliberalism Against Society? Spontaneous Order and Governance of Desire in Digital Societies
Authors: Mavelli Luca , Cerella Antonio
Published: October 2024

Critical scholarship often argues that neoliberalism has caused the ‘crisis’ or ‘destruction’ of society. Drawing on Foucault’s concept of power as ‘productive’ and focusing on digital societies, we argue that neoliberalism seeks not to dismantle society but to create societies that govern desires through market freedom. We explore Friedrich Hayek’s idea that a free society is not based on social well-being or equality, but on spontaneous norms arising from the market order. Digital societies, we contend, are neoliberal but not spontaneous; they emerge from the market order yet are shaped by algorithmic codes that intercept, manipulate, amplify, and promote the voluntary self-exploitation of individual desires. The article combines the latest critical scholarship on neoliberalism with a fresh interpretation of Hayek’s thought and recent work on digital societies and algorithmic governance, highlighting the often-overlooked role of desire in the neoliberal governance of the digital age.
Addressing unpredictable movements of dynamic obstacles with deep reinforcement learning to ensure safe navigation for omni-wheeled mobile robot
Authors: Sachan Saurabh , Pathak Pushparaj Mani
Published: October 2024

The safe and efficient navigation of mobile robots in the presence of unknown dynamic obstacles remains a complex and unresolved challenge. This paper presents collision-free path planning for a mobile robot that safely deals with multi-directional obstacles, that is, randomly moving dynamic obstacles, using a Deep Reinforcement Learning (DRL) algorithm named Deep Q-Network (DQN) with inflated robot reward functions. The robot moves in a time-efficient and collision-free route while maintaining a safe distance with both static and unpredictable dynamic obstacles. The modified DQN algorithm takes RGB images of the environment as input for training a Convolution Neural Network (CNN) and provides a safe and short path for navigation. The robot used for training is an omni-wheeled mobile robot exploring outdoors, that is, concourse environment, and indoors, that is, home environment. The Closed-Loop Inverse Kinematics (CLIK) algorithm is employed to control a mobile robot to follow the desired path. The simulation results indicate that the proposed algorithm with inflated robot reward functions demonstrates remarkable performance as compared to recently used Reinforcement Learning (RL) algorithms when dealing with both stationary and randomly moving obstacles in the given environment.
Effect of shaft deflection on the dynamic behaviors of the ceramic bearing rotor system within wide temperature ranges
Authors: Bai Xiaotian , Yang Wuzhe , Shi Huaitao , Zhang Ke , Luo Zhong , Zheng Hao , Niu Siqi
Published: October 2024

The shaft deflection has great impact on the dynamic characteristics of the ceramic bearing rotor system, which cannot be ignored within wide temperature ranges. This paper establishes a model considering the shaft deflection, and the impact of shaft deflection appears along with changes in bearing attitude. The interaction between the various components of the bearing is recalculated, and the dynamic behavior of the full ceramic bearing rotor system in wide temperature ranges is obtained based on the thermal deformation difference. The trends of dynamic behaviors with rotor mass, rotation speed and shaft length-diameter ratio are investigated, and comparisons between simulation and experimental results are conducted for verification. It is found that the shaft deflection makes impact by bringing in extra centrifugal force, and the effects are reflected in frequency components and trajectories. The simulation results with shaft deflection fit well with the experimental results, which proves that the dynamic model considering the shaft deflection better illustrates the dynamic behavior of the ceramic outer ring when the contact situations change with working temperature. The research carries out deep insight into the running of ceramic bearing rotor system, and provides guidance for the improvement of dynamic behaviors in wide temperature ranges.
Research on robust decision making for intelligent connected vehicle at highway on-ramp
Authors: Fang Huazhen , Liu Li , Gu Qing , Xiao Xiaofeng , Meng Yu
Published: October 2024

Reinforcement learning has demonstrated its potential in the decision-making field of autonomous driving. By engaging in trial-and-error learning and interacting with the environment, we can adapt our behavioral strategies based on reward and enhance driving decisions. Nevertheless, real-world vehicle decision-making involves intricate and diverse information, and the limited state information hinders agents from making optimal decisions, which may result in catastrophic consequences like collisions. Therefore, this paper proposes a robust deep reinforcement learning method based on the Soft Actor-Critic (SAC) algorithm for highway intelligent connected vehicle ramp merging decision-making. The model represents the vehicle features of the target lane and its adjacent lanes as an environmental state space. Additionally, a hybrid action space is designed, which combines discrete lateral actions and continuous longitudinal actions. Finally, an on-ramp simulation platform is built using actual roads and SUMO to verify the feasibility of the model. Multiple sets of comparative analysis experimental results demonstrate that the proposed method outperforms others in terms of the average reward return value, robustness value, collision rate, and success rate. Moreover, the model exhibits a stable lane change success rate under various road traffic density conditions, which indicates its robustness. The code can be obtained at https://github.com/ColinFanghz/sac-on-ramp.git .
Energy-saving cruise control method for heavy-duty transport vehicle based on pump-valve coordinated drive
Authors: Wang Huashuai , Zhang Yanbin , Liu Rongsheng
Published: October 2024

In order to realize the dual-goal of the improvement in the cruise performance and fuel economy of the heavy-duty transport vehicle (HDTV) for the transfer of the prefabricated box-girder in the construction of high-speed railway, a pump-valve parallel coordinated drive scheme is designed on the basis of the hydrostatic drive system of the HDTV, which combines the load-sensing valve control system and hydrostatic pump control system. Furthermore, the pump-valve coordinated controller (PVC) is also proposed to ensure the cooperation of the two systems, which adopts power following control strategy to control engine speed, the pump and motor displacement respectively, thus achieving the rough adjustment of the cruise velocity. The linear quadratic regulator (LQR) based on the full-state closed-loop feedback is introduced in PVC to control the proportional direction-valve (EPDV) and compensate for the velocity errors, thus realizing the fine adjustment of cruise velocity. A semi-physical experimental test-platform for the HDTV is established to conduct contrast tests between the rule-based controller (RBC) and the proposed PVC under different operating conditions. The results indicate that the PVC effectively reduces the velocity error, the total error is decreased by 80.6% and that of the maximum error is 43.4% under empty-load conditions, and under heavy load conditions, the total error is lowered by 82.1% and that of the maximum error is 46.8%. Moreover, the PVC also brings down the fuel consumption rate of the HDTV, with a maximum reduction of 27.6% and a minimum of 11.4%.
Research on the potential of integrated vehicle control with closed-loop phase portrait analysis
Authors: Li Runfeng , Liu Weilong , Sun Yiwen , Lu Ziwang , Tian Guangyu
Published: October 2024

The phase portrait is an important tool for analyzing vehicle stable region widely utilized in vehicle dynamic control systems. At handling limits, traditional open-loop vehicle stable region constraints will restrict the vehicle control ability, while the closed-loop actuator interventions can help states outside the open-loop stable region converge back to stable origin, which is more suitable for constraining vehicle states under extreme working conditions. This article systematically analyzes the potential of integrated vehicle control with closed-loop phase portrait. Firstly, a vehicle dynamic model considering actuator dynamics and tire transient characteristics is established. Then, a numerical optimal control method for calculating closed-loop controllability region is introduced. The controllability region under different friction coefficients, vehicle speeds, convergence time, vehicle steering response characteristics, actuator time constants, and tire transient characteristics are discussed and analyzed. In terms of different control inputs combinations, this article displays the controllability regions under different front steering angles, rear steering angles, direct yaw moments, and their synergistic performances. Control input laws derived from numerical optimization are summarized in two specific directions. Finally, a comparative analysis of open-loop stable regions and closed-loop controllability regions confirms the superiority of the proposed method. Potential applications of the systematic analysis are also discussed.
The intelligent operation and maintenance method and experimental research of CNC machine tool bearings
Authors: Wang Shuo , Yu Zhenliang , Huo Fengwei , Lu Changguo , Wang Jingbo
Published: October 2024

As the core components of high-precision rotary machine tools, machine tool bearings are prone to failure or damage, and their running state directly affects the safety and reliability of the entire equipment. Therefore, the paper proposes an intelligent operation and health management method for machine tool bearings based on Bayes-VMD-KPCA, Bayes-CNN-SVM, and health status evaluation index. Aiming at the complex working environment and high nonlinear degree of fault features of machine tool bearings, the Bayes-VMD-KPCA algorithm is used to perform variational mode decomposition of the original signal of the bearing fault, which avoids the influence of background noise and solves the problem of high dimension of multi-domain fault feature set. Second, the CNN-SVM fault diagnosis model uses a convolutional neural network (CNN) to deeply mine the extracted multi-domain fault features, and a support vector machine (SVM) can be used as a fault classifier to complete the diagnosis of various fault types of machine tool bearings. At the same time, the Bayes algorithm is introduced to tune the hyperparameters in the CNN-SVM model to further improve the prediction performance of the CNC machine tool-bearing fault diagnosis model. The results show that the intelligent operation and maintenance and health management method of CNC machine tool bearings proposed in this paper can effectively complete the fault type diagnosis and health status assessment of bearings, and its accuracy index reaches 99.33%. Compared with the single SVM model, Bayes-CNN model, Bayes-SVM model, and CNN-SVM model, the health effect is evaluated. The accuracy is increased by 6.33%, 4.33%, 2.66%, and 1%, respectively. It can be seen that the proposed method can more effectively realize the monitoring and health management of bearing fault.
‘Retire, play petanque, take synthrom, travel, eat a blue pill and screw two old ladies’: Ageist language in Spain on Twitter
Authors: Gómez-Camacho Alejandro , Moreno-Fernández Olga
Published: October 2024

Ageist language discriminates against older people, infantilising, depersonalising and dehumanising them. Through a longitudinal study of tweets written in Spain between 2019 and 2023, this study investigates the evolution of ageism in the Spanish language. Using a mixed methodology based on Twitter public data mining, 27,971 tweets were analysed. Of these, 3555 tweets (19.31%) used ageist language. The analysis revealed a significant increase in ageist language after COVID-19, with the number of ageist tweets almost doubling compared to the pre-pandemic period. The results of the study suggest that ageist language on Twitter in Spain is mainly characterised by depersonalisation, portraying older people as a homogeneous and passive group. The study also highlights the double discrimination faced by older women on Twitter, where the language is not only ageist but also sexist, limiting their privacy and denying their rights in relation to their sexuality and physical appearance.
Evaluating Predictors of Quality in Liver NK Cells Among Deceased Donors
Authors: Imaoka Yuki , Ohira Masahiro , Nakayama Toshihiro , Akabane Miho , Tajima Tetsuya , Yokota Shinichiro , Krams Sheri M. , Martinez Olivia M. , Esquivel Carlos O. , Sasaki Kazunari , Ohdan Hideki
Published: October 2024

This study investigated the substantial variability in the quality of liver natural killer (NK) cells from deceased donors (DDs). This study assessed liver nonparenchymal cells from 51 DDs for activation receptors and cytotoxicity against K562 (leukemia) and HepG2 (hepatoma) cell lines. The results indicated variability in TNF-related apoptosis-inducing ligand (TRAIL) and NK stimulatory receptor NK group 2 member D (NKG2D) expression in liver NK cells from DDs, which correlated with cytotoxicity against tumor cell lines. In addition, the white blood cell (WBC) count, aspartate aminotransferase (AST) level, body mass index (BMI), and platelet count were significantly associated with enhanced TRAIL and NKG2D expression. A predictive score integrating AST/platelet ratio index, BMI, and WBC count was developed to effectively identify DDs with high antitumor activity in liver NK cells. This score is expected to predict DDs with high-quality liver NK cells, which can be used for the purpose of immunotherapies.
The Career Support Scale for Women in Engineering (CSS-WE): Development and Validation With Engineering Students in Korea
Authors: Kim Jeong-Eum , Lee Hang-Shim , Flores Lisa Y. , Ryu Seong Woo
Published: October 2024

Career supports play a more critical role in the persistence of engineering students relative to perceived barriers, especially among women engineering students ( Fouad et al., 2016 ). Although vocational research on the academic and career development of women in engineering has grown in recent years in response to longstanding and persistent gender disparities in this field, there is a lack of gender-specific instrumentation to assess the perceived supports among women students. This study developed a 21-item Career Support Scale for Women in Engineering (CSS-WE) to assess the perceived supports of Korean women college students pursuing engineering. Using two independent samples of women engineering students, exploratory ( n = 306) and confirmatory ( n = 309) factor analyses supported a five-factor model of the CSS-WE: instrumental support, inclusive support, emotional support, informational support, and institutional and societal support. The results suggested that CSS-WE scores demonstrated strong internal consistency and construct validity. Implications for practice and future research related to supporting women students in engineering are discussed.
Method for enhancing fault feature signals of rolling bearings in gas turbine engines
Authors: Zhao Junhao , Sha Yundong , Luan Xiaochi , Tong Xinyu , Zhang Zhenpeng
Published: October 2024

Aiming at the problem that the weak fault signal of rolling bearings in gas turbine engines (GTEs) is affected by environmental noise, which leads to the difficulty of effective information extraction and easy to ignore, the characterization method for cyclic extraction of main bearing fault feature components in GTEs is proposed. The proposed method begins by subjecting raw vibration signals to wavelet packet decomposition and correlating correlation coefficient and kurtosis values for each node component. These values are then normalized and amalgamated into a comprehensive parameter denoted as P. Subsequently, a confidence interval is established to categorize node components into three groups: high signal-to-noise ratio signals, low signal-to-noise ratio signals, and high-noise signals. Then, the high signal-to-noise ratio signals are continuously filtered according to the feature component cyclic extraction criterion until the termination condition is reached. Finally, all high signal-to-noise ratio signals are reconstructed, followed by envelope demodulation to extract subtle bearing fault characteristics. The findings underscore the efficacy of this approach in extracting fault features within the intricate transmission path of rolling bearings, offering a robust solution for the intricate signal processing and diagnosis of complex rolling bearing faults in GTEs.
Time and Flesh: Exploring the Embodied Experiences of Black Mothers
Authors: Tucker Amber
Published: October 2024

Drawing on Black feminist theories of intersectionality and concepts of temporality and embodiment, this study centers Black girlhood to understand Black girls embodied journeys of “becoming” Black women. Findings revealed that: (a) Black girls often have complicated histories that lead to constrained and liberatory choices in adulthood and motherhood; (b) becoming a Black woman involves continual adaptations to temporal and historical contexts; and (c) Black motherhood is a contested space, deeply shaped by remembering Black girlhood and navigating maternal responses to legacies of harm. This study highlights the challenges and strengths in the transitory states of Black womanhood.
An Inclusive History of LGBTQ+ Aversion Therapy: Past Harms and Future Address in a UK Context
Authors: Davison Kate , Hubbard Katherine , Marks Sarah , Spandler Hel , Wynter Rebecca
Published: October 2024

From the 1950s, aversion therapy gained an international foothold as a behaviourist means to alter what was then considered ‘deviant’ behaviour. Using primary research by psychologists, psychiatrists and other clinical figures published in professional journals, recently published personal testimonies by those who underwent such ‘treatment’, and drawing on the latest historical research, this article maps aversion therapy practices used to ‘treat’ LGBTQ+ people in the UK, mainly in the 1960s and 1970s. We outline our approach to this history and contextualise it by drawing attention to ongoing comparative issues of banning LGBT conversion therapy in the present. Next, we outline the emergence of aversion therapy internationally and identify historical ‘hotspot’ hospitals and universities in the UK, with the nation itself an international ‘hotspot’ for aversion. We then employ the case study of the 2022 report from the University of Birmingham, to demonstrate how such investigations of difficult pasts might be most effectively realised and highlight the potential for a ‘truth and reconciliation’ approach to this history. Finally, we call upon psy-organisations, university and research institutions, and other stakeholders to take this history seriously in effort to address past and ongoing harms enacted upon LGBTQ+ people.
Integrating ytopt and libEnsemble to autotune OpenMC
Authors: Wu Xingfu , Tramm John R , Larson Jeffrey , Navarro John-Luke , Balaprakash Prasanna , Videau Brice , Kruse Michael , Hovland Paul , Taylor Valerie , Hall Mary
Published: October 2024

Ytopt is a Python machine-learning-based autotuning software package developed within the ECP PROTEAS-TUNE project. The ytopt software adopts an asynchronous search framework that consists of sampling a small number of input parameter configurations and progressively fitting a surrogate model over the input-output space until exhausting the user-defined maximum number of evaluations or the wall-clock time. libEnsemble is a Python toolkit for coordinating workflows of asynchronous and dynamic ensembles of calculations across massively parallel resources developed within the ECP PETSc/TAO project. libEnsemble helps users take advantage of massively parallel resources to solve design, decision, and inference problems and expands the class of problems that can benefit from increased parallelism. In this paper we present our methodology and framework to integrate ytopt and libEnsemble to take advantage of massively parallel resources to accelerate the autotuning process. Specifically, we focus on using the proposed framework to autotune the ECP ExaSMR application OpenMC, an open source Monte Carlo particle transport code. OpenMC has seven tunable parameters some of which have large ranges such as the number of particles in-flight, which is in the range of 100,000 to 8 million, with its default setting of 1 million. Setting the proper combination of these parameter values to achieve the best performance is extremely time-consuming. Therefore, we apply the proposed framework to autotune the MPI/OpenMP offload version of OpenMC based on a user-defined metric such as the figure of merit (FoM) (particles/s) or energy efficiency energy-delay product (EDP) on Crusher at Oak Ridge Leadership Computing Facility. The experimental results show that we achieve the improvement up to 29.49% in FoM and up to 30.44% in EDP.
Multicategory Survival Outcomes Classification via Overlapping Group Screening Process Based on Multinomial Logistic Regression Model With Application to TCGA Transcriptomic Data
Authors: Wang Jie-Huei , Hou Po-Lin , Chen Yi-Hau
Published: October 2024

Objectives:

Under the classification of multicategory survival outcomes of cancer patients, it is crucial to identify biomarkers that affect specific outcome categories. The classification of multicategory survival outcomes from transcriptomic data has been thoroughly investigated in computational biology. Nevertheless, several challenges must be addressed, including the ultra-high-dimensional feature space, feature contamination, and data imbalance, all of which contribute to the instability of the diagnostic model. Furthermore, although most methods achieve accurate predicted performance for binary classification with high-dimensional transcriptomic data, their extension to multi-class classification is not straightforward.

Methods:

We employ the One-versus-One strategy to transform multi-class classification into multiple binary classification, and utilize the overlapping group screening procedure with binary logistic regression to include pathway information for identifying important genes and gene-gene interactions for multicategory survival outcomes.

Results:

A series of simulation studies are conducted to compare the classification accuracy of our proposed approach with some existing machine learning methods. In practical data applications, we utilize the random oversampling procedure to tackle class imbalance issues. We then apply the proposed method to analyze transcriptomic data from various cancers in The Cancer Genome Atlas, such as kidney renal papillary cell carcinoma, lung adenocarcinoma, and head and neck squamous cell carcinoma. Our aim is to establish an accurate microarray-based multicategory cancer diagnosis model. The numerical results illustrate that the new proposal effectively enhances cancer diagnosis compared to approaches that neglect pathway information.

Conclusions:

We showcase the effectiveness of the proposed method in terms of class prediction accuracy through evaluations on simulated synthetic datasets as well as real dataset applications. We also identified the cancer-related gene-gene interaction biomarkers and reported the corresponding network structure. According to the identified major genes and gene-gene interactions, we can predict for each patient the probabilities that he/she belongs to each of the survival outcome classes.
Party polarization in digital fingerprints: Tracing politicians’ social media posts on the George Floyd protests
Authors: Park Yul Min , Charm Theodore
Published: October 2024

Under what conditions do politicians express their views on social media? How do politicians express their opinions around a given issue on social media? This paper contends that issue ownership and electoral accountability are critical factors that drive politicians’ attitudes toward a politically salient issue. It conducts a case study on the 2020 George Floyd protests in the United States, using an original, computationally-gathered dataset of posts on Twitter. The multi-level analysis results suggest that politicians’ race and party affiliation, in conjunction with their constituencies’ partisan orientation and racial composition, played significant roles in determining the frequency of Floyd-related Twitter posts they shared. Additionally, topic modeling results demonstrate a disparity in how the political movement is phrased between Democrats and Republicans. These findings shed light on the motivations behind social media posting behavior by public officials and carry significant implications for party polarization in contemporary democracies.
Efficient data-driven nonlinear system identification for structural health monitoring: A proof-of-principle study
Authors: Li Shanwu , Jin Xiaowei , Laima Shujin , Li Hui
Published: October 2024

Structural health monitoring (SHM) is the process of detecting damage in structures. Typically, the damage-sensitive feature identification is based on fitting some models to the measured system response data. The parameters of these models or the prediction errors associated with these models then become the desired damage-sensitive features. Real-world structures usually exhibit significant nonlinear behaviors. Data-driven nonlinear system identification (NSI) is essential to obtain accurate models of structural dynamics for reliable damage detection. However, on the one hand, the data acquisition of real-world structures for damage detection is usually difficult or scarce. On the other hand, NSI generally needs to solve a nonlinear optimization problem that requires more computational time for convergence than linear system identification. Data efficiency and computational efficiency become two critical challenges in data-driven NSI. To address these challenges, this work presents a proof-of-principle study on developing a meta learning-based method for efficient data-driven NSI. Specifically, the meta learning algorithm leverages a previously collected database of similar but different systems to learn the meta-knowledge about how to identify a new system, enabling a fast identification/modeling with limited data. Numerical simulations are performed to validate the method on fundamental nonlinear dynamical systems widely seen in civil engineering. It is observed that the presented meta learning-based method outperforms the conventional method in terms of both data and computational efficiency. Limitations of this work are further discussed.
Trends of fully alcohol-attributable mortality rates before and during COVID-19 in the Baltic and other European countries
Authors: Rehm Jürgen , Tran Alexander , Hassan Ahmed Syed , Jiang Huan , Lange Shannon , Reile Rainer , ŠtelemĖkas Mindaugas
Published: October 2024

Aims:

We tested the polarization hypothesis, which postulates that during times of crises, such as the COVID-19 pandemic, alcohol consumption increases among the heaviest drinkers but decreases among most other drinkers, resulting in an overall decrease in consumption among the population. We posited the increase in heavy drinking would lead to increases in 100% alcohol-attributable (AA) mortality. Furthermore, based on the high level of alcohol consumption in the Baltic countries compared to other European countries, we predicted that the increases in AA mortality would be more pronounced in these countries.

Methods:

Data for 100% AA deaths were obtained from the World Health Organization for the period 2010 to 2022, and standardized to the regional age distribution for 2010. Parametric and non-parametric tests were used to test the study hypotheses.

Results:

The mean age-standardized 100% AA mortality rate increased during the COVID-19 pandemic in the 19 European countries with data by 3.12 deaths per 100,000 population, constituting an 18% increase (tested against no change: t = 2.52; df = 18; p = 0.021). This increase was higher in the Baltic countries (mean difference = 13.41 deaths per 100,000 population; standard deviation (SD) = 7.44; 46% increase) than for other European countries (mean difference = 1.19; SD = 1.55; 8% increase). The increases in 100% AA mortality were associated with decreases in the level of alcohol consumption in the majority of countries.

Conclusions:

As predicted, 100% AA mortality increased in 19 European countries during the COVID-19 pandemic, with the Baltic countries seeing a higher increase. Renewed alcohol control policy efforts should be considered.
What’s a news media brand worth? Investigating the effect of cognitive brand representations on recipients’ quality assessment of news articles
Authors: Leuppert Robin , Bruns Sophie , Rahe Vanessa , Scherer Helmut
Published: October 2024

News recipients evaluate the quality of journalistic news articles based on the article’s journalistic quality and its media brand. We argue that differentiating a news media’s brand identity from recipients’ cognitive associations with the brand offers a valuable perspective to understand quality evaluations in a more detailed way. We, therefore, specify the effect of media brands on the quality evaluation by including consumer-based brand equity (CBBE) as a mediator and investigate this mediation effect for five quality dimensions and a global quality measure. Based on a two (high vs low quality) x three (quality brand vs tabloid brand vs control group) between-subject experiment with 469 German respondents, we conducted structural equation modeling to investigate the direct effects of media brands on recipients’ quality assessment of news articles and the mediating effect via CBBE. We found mediation effects of the media brand via CBBE on all quality dimensions and the global measure. In addition, two direct media brand effects with opposite effect directions than expected could be identified. All results are discussed concerning further theory development and practical implications.
A semi-empirical model for online real-time control of NOX generation in diesel engines
Authors: Ma Xuejian , Qiu Tao , Lei Yan , Liu Zedu , Chen Zexun , Fu Jun
Published: October 2024

Diesel NOX emission control is the main control content of diesel engines. Real-time high-precision NOX emission prediction model is the basic guarantee for (1) Diesel combustion management, (2) SCR after-treatment control, (3) OBD system. Existing models that rely exclusively on physical processes or data-driven artificial intelligence models fail to meet real-time requirements, while MAP look-up table-based models are poorly adapted and require extensive experiments for calibration. In this study, a new semi-empirical model for NOX emission prediction was developed, and the variables of the model were identified as exhaust temperature, engine speed, injected fuel mass flow rate, air intake mass flow rate, and exhaust oxygen mass flow rate, taking into account the mechanism of NOX generation in diesel engines as well as the requirement of real-time and direct measurability of the variables for on-line control. The influence of each variable on NOX was analyzed, the model structure of the NOX prediction model was determined, and the parameters of the prediction model were identified by least squares. The model is applied to real operating vehicles for validation and compared with a previous semiempirical model taken from the literature, and the results show that the overall accuracy of the proposed model is improved. Finally, the effect of variable uncertainty on the proposed model was assessed and it was found that the relative uncertainty in predicting NOX emissions ranged between 0 and 8% for sensor accuracies of [Formula: see text] and [Formula: see text] for exhaust temperature and intake air mass flow, respectively, suggesting that the sensor accuracy has a significant effect on the uncertainty of the model.
Claiming rock art, claiming indigeneity: Spaces and scales of recognition in Khoe and San identity claims
Authors: Quemin Hugo , Duval Mélanie , Lahaye Romain
Published: October 2024

Based on research conducted in South Africa, this work revolves around the observation that certain rock art sites (Wildebeest Kuil, Northern Cape; Game Pass Shelter, KwaZulu-Natal) are utilized within identity and political frameworks—and a question: what role do rock art sites play in the construction of Khoe and San indigeneity? Contemporary indigeneity is closely linked to issues of recognition, which are themselves related to the restitution of rights, objects, and knowledge. Acknowledging the central role of objects in identity claims, this article proposes to analyze the place of these two rock art sites in the political construction of Khoe and San indigeneity. Based on a corpus of interviews, observations, legal texts, and press articles, certain uses of rock art sites will be presented as strategic means within a broader context of claims.
Showing climate action: exploring Fridays for Future Germany’s visual activism on Flickr
Authors: Shim David
Published: October 2024

This article examines how Fridays for Future Germany (FFFG) uses photographs of climate protests to convey the politics of climate change to wider audiences. The author argues that FFFG is an ideal-type form of visual activism in which visual imagery is central to its climate activism. The article builds on climate change communication scholarship and visual social movement studies to contribute an inquiry about FFFG’s visual activism. The focus is on FFFG’s visual self-representations on the social media platform Flickr, which promises to give insights into its strategies of self-legitimation. The empirical analysis discusses the recurring visual patterns in FFFG’s visual activism based on illustrative examples and provides an interpretive reading about the implications of certain ways of seeing and showing climate action. The conclusion puts the findings in a wider political context, highlighting the importance of visualization in the (self-)legitimation of FFFG in debates about global climate governance.
High Intrapatient Tacrolimus Variability and Increased Cell-Free DNA in Kidney Transplant Recipients
Authors: Kopfman Miranda , Brokhof Marissa , Patel Shree , Fu Dennis , Olaitan Oyedolamu
Published: October 2024

Introduction: An inverse relationship has been identified between tacrolimus serum concentrations and donor-derived cell-free DNA (dd-cfDNA) levels after lung transplant, but limited data exists on this relationship in the kidney transplant population. Project Aim: The purpose of this evaluation was to examine the relationship between high tacrolimus variability and elevated dd-cfDNA levels in kidney and simultaneous pancreas-kidney transplant recipients at a single center. Design: Single-center, retrospective, descriptive comparative evaluation of kidney and pancreas-kidney transplant recipients who received longitudinal ddcfDNA surveillance. Intrapatient tacrolimus variability was assessed using the coefficient of variation (%CV) measured between 1 and 12 months posttransplant. Pediatrics, retransplant or multiorgan transplant recipients, and pregnant recipients were excluded. Results: One hundred fifteen recipients with 518 dd-cfDNA levels and 3028 tacrolimus troughs were assessed. Pancreas-kidney recipients had significantly higher median dd-cfDNA (0.29% vs. 0.18%, P = .034) and were excluded from analysis. Ninety-nine kidney transplant recipients were included for analysis. Recipients with tacrolimus %CV ≥30 ( N = 66) had significantly higher median dd-cfDNA than %CV <30 (0.22% vs. 0.17%, P = .031). Tacrolimus %CV ≥30 demonstrated higher median peak dd-cfDNA than %CV <30, though this was not statistically significant (0.36% vs. 0.28%, P = .058). Conclusion: These data demonstrated that high intrapatient tacrolimus variability may be associated with elevated dd-cfDNA in the first year after kidney transplant.
Gastric Cancer Signaling Pathways and Therapeutic Applications
Authors: Wu Mingfang , Yuan Shiman , Liu Kai , Wang Chenyu , Wen Feng
Published: October 2024

Gastric cancer (GC) is a prevalent malignant tumor and ranks as the second leading cause of death among cancer patients worldwide. Due to its hidden nature and difficulty in detection, GC has a high incidence and poor prognosis. Traditional treatment methods such as systemic chemotherapy, radiotherapy, and surgical resection are commonly used, but they often fail to achieve satisfactory curative effects, resulting in a very low 5-year survival rate for GC patients. Currently, targeted therapy and immunotherapy are prominent areas of research both domestically and internationally. These methods hold promise for the treatment of GC. This article focuses on the signaling pathways associated with the development of GC, as well as the recent advancements and applications of targeted therapy and immunotherapy. The aim is to provide fresh insights for the clinical treatment of GC.
Does Sperm DNA Fragmentation Index Continuously Decrease Over Time After Varicocelectomy in Varicocele-Induced Infertility? A Systematic Review and Meta-Analysis
Authors: Wang Lihong , Zheng Lei , Jiang Hui , Jiang Tao
Published: October 2024

Varicocele (VC) is the most frequent and reversible cause of male infertility. One of the preferred management strategies to alleviate this problem is varicocelectomy. However, there are no researchers who have explored the relationship between better timing and postoperative sperm DNA fragmentation index (DFI) improvement in patients. We conducted this meta-analysis by enrolling published studies to find out the best waiting time after varicocelectomy to wait for better improvement of sperm DFI. A literature search was conducted using PubMed, Embase, Scopus, Web of Science, and Cochrane Library databases. The data from the pooled analysis were presented as mean difference (MD) along with a 95% confidence interval (CI). Heterogeneity was evaluated using I2. Four studies were included after screening relevant literature. Statistical analysis revealed that after varicocelectomy, follow-up results within 3 months showed a significant improvement in sperm DFI compared with the preoperative period (MD: –3.66, 95% CI = [–5.17, –2.14], p < .00001), and follow-up results with 6 months showed a significant improvement in sperm DFI compared with the postoperative 3 months as well (MD: –1.51, 95% CI = [–2.73, –0.29], p = .02). Notably, no further improvement in sperm DFI was observed when the follow-up period reached 12 months (MD: –1.59, 95% CI = [–3.22, 0.05], p = .06). Six months after varicocelectomy may be the optimal time for sperm DFI compared with 12 months or even longer, which means it is also the preferable time for conception. However, more well-designed prospective studies are needed in the future to validate our conclusion.
Exploring the Mechanism of Action of Sericin in Ameliorating non-Alcoholic Fatty Liver Disease in Mice Based on the Nrf2- GPX4/ NF-κB p65 Pathway
Authors: Li Jinyue , Yi Dan , Gao Yuqiu , Zhou Lihong , Wen Pingjing , Qin Guangqiu
Published: October 2024

Objective: To explore the ameliorative effect and mechanism of action of sericin on liver injury in Non-Alcoholic Fatty Liver Disease (NAFLD) model mice. Methods: Mice were fed a high-fat diet for 8 weeks to establish NAFLD model mice. The NAFLD mice were then randomly divided into 6 groups and given 0, 250, 500, and 1000 mg/kg body weight of sericin, 1000 mg/kg sericin + ML385 (a protein inhibitor of Nrf2), and Zhibitai Capsules (a positive drug), by gavage, respectively. The levels of TC, TG, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) in mouse serum and the levels of MDA, GSH, SOD, TNF-α, and IL-6 in liver tissues were measured. Pathological changes in liver tissues were evaluated using hematoxylin-eosin (HE) and Oil Red O staining. Protein expression of Nrf2, Keap1, HO-1, GPX4, and NF-κB p65 in liver tissues was detected by Western blotting, and the expression level of GPX4 in the liver was examined by immunohistochemistry. Results: Sericin and Zhibitai Capsules improved hepatic steatosis and lipid accumulation in NAFLD model mice. TC, TG, LDL-C, MDA, and TNF-α, IL-6 levels were down-regulated, and HDL-C and SOD levels were up-regulated. There was no significant difference in the expression of AST and ALT in all the groups. In addition, Sericin and Zhibitai Capsules upregulated the expression levels of Nrf2, keap1, HO-1, and GPX4 proteins and inhibited the expression of NF-κB p65 in the liver of NAFLD model mice. There was no significant difference in serum lipids and liver indices between the 1000 mg/kg sericin + ML385 group and the sericin dose groups. Conclusion: Sericin has an ameliorative effect on liver injury in NAFLD model mice by alleviating oxidative stress and inflammatory responses in liver injury. It remains to be explored whether this effect is regulated through the Nrf2- GPX4/ NF-κB p65 signaling pathway.
Antioxidant and Immunological Properties of Dracocephalum moldavica Extract in Penaeus vannamei
Authors: Adelnina Najmeh , Mosavi Dehmordi Laleh , Amini Chermahini Mohammad , Sori Morteza
Published: October 2024

Objectives: The effects of different concentrations of Dracocephalum moldavica extract (DME) supplement on growth, survival, antioxidants, some biochemical parameters and innate immunity of White leg shrimp (Penaeus vannamei) juveniles investigated. Methods: For 56 days, shrimp (4.5-5 g) received diets that were enhanced with 0 (control), 50, 100, 200 mg DME/kg feed to attain apparent satiety. Results: The results revealed that feeding shrimp with DME significantly improved Feed efficiency and Feed conversion ratio with an optimum level of 200 mg/kg diet. Dietary DME supplementation had no significant effects on their carcass composition. Total albumin and protein higher (P > 0.05) in DME-fed particularly at 200 mg/kg treatment On the other hand, shrimp fed 200 mg DME/kg feed experienced significant decreases in aspartate and alanine aminotransferase levels. As dietary extract levels increased, there was a significant (P < 0.05) increase in SOD and CAT activities, as well as LYZ and PO levels, so that treatments with 100 and 200 mg DME/kg feed had the highest values, and Significant (P < 0.05) reductions in MDA and NO levels were observed at high dietary extract levels of 100 and 200 mg DME/kg. Conclusion: P. vannamei's growth, antioxidant capacity and innate immunity were boosted by diets that contained 200 mg DME/kg feed.
Instructional Method Shifts: Instructors’ Plans Post Emergency Remote Teaching
Authors: Kaiser Leann M. R. , Lopes Tobin , Manson Michelle , Zarestky Jill , McKenna Kelly , Saade Diana J.
Published: October 2024

The coronavirus pandemic, beginning in 2020, caused significant disruption to higher education around the globe, forcing instructors into emergency remote teaching. This emergency response created unprecedented adaptation to online and distance education processes and activities. Yet, the ways in which those teaching changes influenced or continue to influence teaching in higher education are unknown. This study explores the changes to faculty teaching practices, and associated learning, as a result of emergency remote teaching and faculty plans to continue or discontinue those practices post-pandemic. Quantitative results indicated practices were largely intended to impact cognitive, emotional, behavioral, and social dimensions, social interactions, and learning activities. A significant majority of the practices achieved their intended results and almost two-thirds of the practices will be continued. Qualitative results illustrated a variety of benefits for both students and instructors. These shifts were largely student-centered with noted improvements in areas like flexibility, agency, access, inclusivity, engagement, and connection. Results apply to workplace training and professional development for faculty in higher education and beyond, including ways to engage faculty in valuable teaching practices and support student learning at a distance.
The Incidence of Shoulder and Elbow Injuries in High School and Collegiate Softball Athletes: A Systematic Review
Authors: Enata Nichelle M. , Inclan Paul M. , Brophy Robert H. , Knapik Derrick , Smith Matthew V.
Published: October 2024

Context:

Despite increased youth and adolescent participation in fast-pitch softball and the reporting of upper extremity injuries, there remains a relative paucity of research examining shoulder and elbow injuries in high school and collegiate softball athletes.

Objective:

To evaluate the reported incidence, setting, and positional factors associated with shoulder and elbow injuries in high school and collegiate fast-pitch softball players.

Data Sources:

PubMed, Ovid, Medline, EMBASE, Scopus, Cochrane Central, and Clinicaltrials.gov.

Study Selection:

English-language articles reporting the incidence of shoulder and/or elbow injuries occurring in high school or collegiate fast-pitch softball players were included. Biomechanical studies, review articles, abstract only texts, previous systematic reviews, and meta-analyses were excluded.

Study Design:

Systematic review.

Level of Evidence:

Level 4.

Data Extraction:

Two reviewers independently evaluated studies. Data related to the reported incidence of shoulder and elbow injuries, injury setting, position, and rate of return to play after injury were recorded.

Results:

A total of 22 studies were identified. In high school athletes, shoulder injury rates ranged from 0.88 to 1.14 per 10,000 athletic exposures (AE), with elbow injury rates ranging from 0.41 to 0.71 per 10,000 AE. In collegiate athletes, reported injury rates ranged from 3.76 to 5.93 per 10,000 AE for shoulder and 1.5 to 3.39 per 10,000 AE for elbow injuries. Shoulder and elbow injuries were reported more commonly during competition in high school athletes, and with greater frequency in the practice setting in collegiate athletes. No association between injury incidence and position was appreciated at either the high school or collegiate level. Most (81%-96%) athletes were able to return to sport within 3 weeks of injury.

Conclusion:

The incidence of shoulder and elbow injuries was greater in collegiate softball athletes than in high school athletes.