bluuebunny/crossref_metadata_2025_split huggingface dataset:
Perspectives of a non‐medically and a medically qualified early career anatomy academic on facilitating case‐based learning sessions for undergraduate medical students
Authors: Patera Eleni , Adwan Mustafa Mohammedyiya 
Published: August 2024

AbstractCase‐based learning (CBL) is a student‐centered pedagogy where medical students are given a real‐world clinical problem. At St George's University of London (SGUL), anatomy academics can volunteer to facilitate CBL sessions for pre‐clinical undergraduate medical students. The major benefits of facilitating CBL sessions from the perspective of a non‐medically qualified early career anatomy academic (ECAA) include exposure to clinical cases that help the academic develop an understanding over key clinical cases at the context of clinical anatomy and other disciplines including physiology, pathology, and pharmacology. Furthermore, facilitating CBL sessions assists in the acquisition of basic knowledge over history taking, the conduction of clinical examinations, the investigations performed for the diagnosis of a condition as well as how it is managed. The major benefits of facilitating CBL sessions from the perspective of a medically qualified ECAA include staying in touch with the clinical aspect of medicine and becoming familiar with the country's healthcare system and its professional standards. Perceived benefits shared by both the non‐medically and medically qualified ECAA include the opportunity to become familiar with the structure and key elements of the pre‐clinical medical curriculum as well as gain experience in facilitating small group teaching sessions. Overall, facilitating CBL sessions can help non‐medically and medically qualified ECAAs in different contexts that may help them with their individual career goals, can encourage collaborative discussions between clinical and non‐clinical anatomy academics as well as help bridge the gap between the anatomy teaching approaches employed by non‐medically qualified and medically qualified anatomy academics.
Sustainable synthesis of fluorescent polymer carbon dots@PVA for sensitive chlortetracycline detection
Authors: Radhakrishnan Kothalam , Kumar J. Vinoth , Bhagyalakshmi J. , Devanesan Sandhanasamy , Mythili R. , Reddy I. Neelakanta , Bai Cheolho 
Published: August 2024

AbstractAntibiotic residues persist in the environment and represent serious health hazards; thus, it is important to develop sensitive and effective detection techniques. This paper presents a bio‐inspired way to make water‐soluble fluorescent polymer carbon dots (PCDs@PVA) by heating biomass precursors and polyvinyl alcohol (PVA) together. For example, the synthesized PCDs@PVA are very stable with enhanced emission intensity. This property was observed in a wide range of environmental conditions, including those with changing temperatures, pH levels, UV light, and ionic strength. PCDs@PVA detected the antibiotic chlortetracycline (CTCs) with great selectivity against structurally related compounds and a low detection limit of 20 nM, demonstrating outstanding sensitivity and specificity. We confirmed the sensor's practical application through real sample analysis, yielding recovery rates of 98%–99% in samples of milk, honey, and river water. The synthesized PCDs@PVA fluorescence sensor was successfully used for CTCs detection in real samples.
A quantitative method for the analysis of total and unbound concentrations of amoxicillin, ampicillin, ceftazidime, ceftriaxone, ertapenem, fosfomycin and penicillin G in human plasma with liquid chromatography–tandem mass spectrometry assay
Authors: van der Veer Marlotte A. A. , van der Meer‐Vos Marloes , de Haan Timo R. , Franken Linda G. W. , Bijleveld Yuma. A. , Mathôt Ron A. A. 
Published: August 2024

AbstractMonitoring antibiotic plasma levels is critical in populations with altered pharmacokinetics, such as critically ill patients in neonatal or adult intensive care units. This study aimed to develop and validate a rapid, reproducible and sensitive liquid chromatography–tandem mass spectrometry assay (LC–MS/MS) for measuring total and unbound concentrations of amoxicillin, ampicillin, ceftazidime, ceftriaxone, ertapenem, fosfomycin and penicillin G in human plasma. The method required 20 and 250 μl sample volumes for measuring total and unbound concentrations, respectively. Sample preparation involved protein precipitation and the addition of an internal standard. Ultrafiltration separated unbound drugs. Method validation covered selectivity, carryover, linearity, accuracy, precision, dilution effects, matrix effects and stability. The LC–MS/MS was performed within a run time of 7.5 min. Calibration curves were linear for ceftazidime and ertapenem (ranges 0.1–50 and 0.05–100 mg/l, respectively) and quadratic for other analytes (0.1–50 mg/l, except for ampicillin: 0.1–20 mg/l; R2 > 0.990). Accuracy was within ±15% of the nominal concentration, and precision did not exceed ±15% (relative standard deviation). Samples showed no significant degradation at the tested temperatures and time points. Clinical applicability was demonstrated in a critically ill neonate. This method with minimal sample volume and short analysis time enables the measurement of total and unbound concentrations of selected antibiotics, and is suitable for routine clinical care and studies.
Profit first, environmental impact second? Investigating hybrid institutional logics in venture capital investment approaches
Authors: Siefkes Meike , Hamer Anton Lohne , Haaland Gustav , Bjørgum Øyvind 
Published: August 2024

AbstractDespite a potential mismatch between characteristics of cleantech innovations and the venture capital model, there has been a surge of cleantech venture capital firms (VCs). This paper investigates how cleantech VC investment approaches are aligned with hybrid institutional logics. We mapped 36 European VCs regarding their portfolio firms' industries, technology focus, and level of innovation. From this sample, we interviewed nine VC investors to gain a comprehensive understanding of the phenomenon. The findings show a heterogenous landscape of cleantech VC investment approaches. Cleantech VCs finance mostly incremental innovations in highly emissive sectors. For several of the VCs, the findings highlight a disconnect between the externally communicated cleantech mission and lack of approaches for environmental impact management. We develop propositions for future research. This study adds novel empirical perspectives and contributes to the development of hybrid logics in institutional logics theory with a nuanced examination of the European VC cleantech market.
Acceptance of or resistance to facial recognition payment: A systematic review
Authors: Yu Teng , Wang Chengliang , Bian Qing , Teoh Ai Ping 
Published: August 2024

AbstractWith increasing evidence supporting the use of biometric identification methods for authentication, this study aims to enhance our understanding of the factors influencing the acceptance of and resistance to facial recognition payment (FRP) systems. To provide a comprehensive review of these factors, we conducted a systematic literature review (SLR) of empirical studies. We examined 22 key research articles from an initial pool of 1372 publications, identifying 37 factors that influence consumer acceptance or resistance to FRP. These factors were categorized into usage‐related aspects, attitudes and evaluations, user‐related traits, privacy and security concerns, and other factors. Our findings reveal that the most frequently cited factors include performance expectancy, effort expectancy, perceived usefulness, and perceived ease of use. These factors are crucial in contexts where FRP can increase productivity by providing prompt information and effective assistance. This research proposes a collective model for understanding the determinants of FRP acceptance or resistance, integrating theoretical frameworks and empirical findings. The model emphasizes the context‐dependency of user acceptance, highlighting the importance of addressing both technological and psychological factors. It incorporates usage characteristics, user characteristics, and privacy and security concerns, which are mediated by attitudes and evaluations. The proposed model provides a comprehensive framework for understanding and addressing the factors influencing acceptance of and resistance to FRP, guiding FRP service providers in developing effective strategies to increase user adoption, with future research needed to refine and assess the model further.
Synergistic modulation of valence state and oxygen vacancy induced by surface reconstruction of the CeO2/CuO catalyst toward enhanced electrochemical CO2 reduction
Authors: Chang Fangfang , Zhang Zhenmao , Zhang Yan , Liu Yongpeng , Yang Lin , Wang Xiaolei , Bai Zhengyu , Zhang Qing 
Published: August 2024

AbstractElectrochemical CO2 reduction reaction (CO2RR) offers a promising strategy for CO2 conversion into value‐added C2+ products and facilitates the storage of renewable resources under comparatively mild conditions, but still remains a challenge. Herein, we propose the strategy of surface reconstruction and interface integration engineering to construct tuneable Cu0–Cu+–Cu2+ sites and oxygen vacancy oxide derived from CeO2/CuO nanosheets (OD‐CeO2/CuO NSs) heterojunction catalysts and promote the activity and selectivity of CO2RR. The optimized OD‐CeO2/CuO electrocatalyst shows the maximum Faradic efficiencies for C2+ products in the H‐type cell, which reaches 69.8% at −1.25 V versus a reversible hydrogen electrode (RHE). Advanced characterization analysis and density functional theory (DFT) calculations further confirm the fact that the existence of oxygen vacancies and Cu0–Cu+–Cu2+ sites modified with CeO2 is conducive to CO2 adsorption and activation, enhances the hydrogenation of *CO to *CHO, and further promotes the dimerization of *CHO, thus promoting the selectivity of C2+ generation. This facile interface integration and surface reconstruction strategy provides an ideal strategy to guide the design of CO2RR electrocatalysts.
Perovskite oxides as electrocatalysts for water electrolysis: From crystalline to amorphous
Authors: Sun Hainan , Xu Xiaomin , Chen Gao , Shao Zongping 
Published: August 2024

AbstractCrystalline perovskite oxides are regarded as promising electrocatalysts for water electrolysis, particularly for anodic oxygen evolution reactions, owing to their low cost and high intrinsic activity. Perovskite oxides with noncrystalline or amorphous characteristics also exhibit promising electrocatalytic performance toward electrochemical water splitting. In this review, a fundamental understanding of the characteristics and advantages of crystalline, noncrystalline, and amorphous perovskite oxides is presented. Subsequently, recent progress in the development of advanced electrocatalysts for water electrolysis by engineering and breaking the crystallinity of perovskite oxides is reviewed, with a special focus on the underlying structure–activity relationships. Finally, the remaining challenges and unsolved issues are presented, and an outlook is briefly proposed for the future exploration of next‐generation water‐splitting electrocatalysts based on perovskite oxides.
Scaling in reverse osmosis seawater desalination: Mechanism and prevention—A literature review
Authors: Shen Jiaxuan , Wang Xiaodong , Zhu Xiaoyi , Tang Bojin , Liu Cong , Li Wan , Gao Xueqiang 
Published: August 2024

AbstractThere is currently a huge imbalance between the demand and supply of freshwater resources. The shortage of fresh water can be mitigated by seawater desalination. Reverse osmosis (RO) is currently the most popular desalination technology around the world. Despite its various advantages, fouling has been one of its major limitations of RO. Membrane fouling can be divided into four categories: colloidal fouling, inorganic fouling, organic fouling, and biofouling. Precipitation of inorganic salts of small solubility, among which CaCO3, CaSO4, BaSO4, and SiO2 are the most common ones, are the cause of inorganic fouling, which is commonly referred to as scaling. Pretreatment technologies for prevention or mitigation of scaling in the RO process can be classified as conventional pretreatment technologies, which include water softening and scale inhibitors, and membrane‐based pretreatment technologies which include nanofiltration, forward osmosis, and membrane surface modification.
Physics‐informed neural networks guided modelling and multiobjective optimization of a mAb production process
Authors: Alam Md Nasre , Anurag Anurag , Gangwar Neelesh , Ramteke Manojkumar , Kodamana Hariprasad , Rathore Anurag S. 
Published: August 2024

AbstractIn this paper, we aim to correlate various process and product quality attributes of a mammalian cell culture process with process parameters. To achieve this, we employed physics‐informed neural networks that solve the governing ordinary differential equations comprising independent variables (inputs‐ time, flow rates, and volume) and dependent variables (outputs‐ viable cell density, dead cell density, glucose concentration, lactate concentration, and monoclonal antibody concentration). The proposed model surpasses the prediction and accuracy capabilities of other commonly used modelling approaches, such as the multilayer perceptron model. It has higher R‐squared (R2), lower root mean square error, and lower mean absolute error than the multilayer perceptron model for all output variables (viable cell density, viability, glucose concentration, lactate concentration, and monoclonal antibody concentration). Furthermore, we incorporate a Bayesian optimization study to maximize viable cell density and monoclonal antibody concentration. Single objective optimization and weighted sum multiobjective optimization were carried out for viable cell density and monoclonal antibody concentration in separate (single objective optimization) and combined (multiobjective optimization) forms. An increment of 13.01% and 18.57% for viable cell density and monoclonal antibody concentration, respectively, were projected under single objective optimization, and 46.32% and 67.86%, respectively, for multiobjective optimization as compared to the base case. This study highlights the potential of the physics‐informed neural networks‐based modelling and optimization of upstream processing of mammalian cell‐based monoclonal antibodies in biopharmaceutical operations.
Evaluation of lamin A/C mechanotransduction under different surface topography in LMNA related muscular dystrophy
Authors: Dutta Subarna , Muraganadan T. , Vasudevan Madavan 
Published: August 2024

AbstractMost of the single point mutations of the LMNA gene are associated with distinct muscular dystrophies, marked by heterogenous phenotypes but primarily the loss and symmetric weakness of skeletal muscle tissue. The molecular mechanism and phenotype–genotype relationships in these muscular dystrophies are poorly understood. An effort has been here to delineating the adaptation of mechanical inputs into biological response by mutant cells of lamin A associated muscular dystrophy. In this study, we implement engineered smooth and pattern surfaces of particular young modulus to mimic muscle physiological range. Using fluorescence and atomic force microscopy, we present distinct architecture of the actin filament along with abnormally distorted cell and nuclear shape in mutants, which showed a tendency to deviate from wild type cells. Topographic features of pattern surface antagonize the binding of the cell with it. Correspondingly, from the analysis of genome wide expression data in wild type and mutant cells, we report differential expression of the gene products of the structural components of cell adhesion as well as LINC (linkers of nucleoskeleton and cytoskeleton) protein complexes. This study also reveals mis expressed downstream signaling processes in mutant cells, which could potentially lead to onset of the disease upon the application of engineered materials to substitute the role of conventional cues in instilling cellular behaviors in muscular dystrophies. Collectively, these data support the notion that lamin A is essential for proper cellular mechanotransduction from extracellular environment to the genome and impairment of the muscle cell differentiation in the pathogenic mechanism for lamin A associated muscular dystrophy.
Blockchain‐based incentive mechanism for environmental, social, and governance disclosure: A principal‐agent perspective
Authors: Niu Yuxiang , Fu Yelin , Liu Xinlai , Harish Arjun Rachana , Li Ming , Huang George Q. 
Published: August 2024

AbstractEnvironmental, social, and governance (ESG) disclosure has drawn much attention from listed companies, investors, and regulators. In response to the increasing demand of investors and regulators for non‐financial information, listed companies have paid attention to publishing ESG reports consisting of environmental, social, and governance information. Listed companies are increasingly required to provide high‐quality information that is clear and comparable. However, the lack of incentive to listed companies makes it hard to improve the quality of ESG disclosure, and the cost of ESG disclosure leads to the uncontrollable quality of ESG reports and may even manipulation by opportunistic behaviors. In this paper, we illustrate the moral hazard problem in ESG disclosure from the perspective of investors and listed companies, in which the effort level for listed companies to provide high‐quality ESG report cannot be observed by investors. Then we propose a blockchain‐based incentive mechanism for ESG disclosure from a principal‐agent perspective to improve the information quality of ESG disclosure, where investors act as principal and listed companies act as agents. Token in blockchain technology is utilized as the rewards to improve the listed companies' reputation, thus increasing their chance of being promoted to investors for preferential investment opportunities in the blockchain platform. We then design the first‐best (FB) and second‐best (SB) optimal contracts based on classic principal‐agent model to overcome the moral hazard problem. Extensive simulations are conducted to demonstrate the effectiveness and feasibility of the incentive mechanism.
Effect of temperature on the wave breaking amplitude of nonlinear relativistic strong plasma waves
Authors: Yadav Govind Singh , Karmakar Mithun 
Published: August 2024

AbstractThe wave‐breaking amplitude of a strong nonlinear plasma wave has been determined in a warm plasma. Pseudopotential technique has been adopted to describe the wave‐breaking phenomena in such plasma. The solution is obtained with the consideration that the phase velocity of the plasma wave is equal to the velocity of light in vacuum. This assumption is justified since the wave which is excited usually by the relativistic charged particle bunches or laser pulses has phase speed very close to the speed of light in vacuum. The investigation shows that the breaking amplitude decreases with the increase of the electron temperature. Furthermore, the wavelength of the plasma wave is seen to decrease as we increase the electron temperature. The obtained results have relevance in the astrophysical situation as well as in the field of plasma based charged particle acceleration process.
Trajectories of opioid use among patients with low back pain: Association to work absence
Authors: Hansen Johan Liseth , Wangen Knut Reidar 
Published: August 2024

AbstractBackgroundLow back pain (LBP) is a leading reason for opioid use and a closer examination of opioid use and productivity losses among these patients is needed. We identify opioid use trajectories using a group‐based trajectory model (GBTM) and estimate productivity losses across the trajectories.MethodsPatients diagnosed with LBP in Swedish specialty care between 2011 and 2015, between the ages of 20 and 60, were included. Two GBTMs were estimated on monthly opioid use (converted to oral morphine equivalents) during the two 12‐month periods preceding and following diagnosis. Productivity losses were estimated using the human‐capital approach.ResultsIn total, 147,035 patients were included. The mean age at diagnosis was 43 years of age and 49% of the patients were male. A qualitative assessment of the identified groups in the GBTM models was made based on the patterns of opioid use. We chose three pre‐diagnosis groups characterized as ‘Pre‐low’ (N = 109,492), ‘Pre‐increase’ (N = 27,336) and ‘Pre‐high’ (N = 10,207). Similarly, four post‐diagnosis groups were chosen and characterized as ‘Post‐low’ (N = 73,287), ‘Post‐decrease’ (N = 39,446), ‘Post‐moderate’ (N = 20,001) and ‘Post‐high’ (N = 13,595). Only 50% of the patients in the ‘Pre‐high’ group were in the ‘Post‐high’ group. The total productivity losses by the pre‐diagnosis groups were more than 2.7 billion Euros over the total 6‐year study period.ConclusionThis study highlights how patients with LBP and high use of opioids are highly correlated before and after diagnosis. Patients with high use of opioids also exhibit high work absence and productivity losses.Significance StatementThis was the first study to estimate trajectories of opioids in the two time periods before and after a diagnosis of low back pain. For the first time, productivity losses were also estimated across the identified opioid use trajectories.
The measurement of “high‐impact chronic pain”: Limitations and alternative methods
Authors: Riddle Daniel L. , Dumenci Levent 
Published: August 2024

AbstractObjectiveChronic pain is known to be an important construct in clinical practice and a particular form of chronic pain, high‐impact chronic pain (HICP), has gained recent interest and attention by pain clinicians, epidemiologists, and clinical researchers. The purpose of our Topical Review is to describe the historical development of measures of HICP and to explore the psychometric properties of HICP as well as to present alternative measurement methods.MethodsWe identified strengths and weaknesses of the psychometric characteristics of HICP measures. Limitations of existing HICP measures were discussed and summarized and alternatives to current methods were proposed.ResultsHICP operational definitions show variability across studies. All definitions cannot be correct, but which ones are incorrect cannot be determined as there is no gold standard. Random measurement error and recall bias are among the other limitations of current HICP measures. Model‐based definitions of HICP, the discrete (for epidemiologic applications) and continuous (for clinical applications) latent variable models are discussed as likely superior alternatives to current methods.ConclusionsLimitations of existing HICP methods are discussed and alternative development approaches to HICP measures are presented. The use of either discrete or continuous latent variable models would improve upon the psychometric characteristics of current HICP evidence. Examples are used to illustrate the benefits of latent variable models over traditional observed variable conceptualizations as the measurement of HICP continues to develop.Significance StatementThis work takes the position that current methods of measuring high impact chronic pain (HICP) likely contain substantial error. We have endorsed an alternative approach for several psychometrically grounded reasons. We recommend that future work consider the discrete latent variable framework for dichotomous measures of HICP and the continuous latent variable framework for continuous measures of HICP. The paper provides illustrative examples of these methods for a different patient reported measure that is lacking a gold standard, much like HICP measures.