bluuebunny/crossref_metadata_2025 huggingface dataset:
The Crack Control Strategy Is Influenced by the Continuous Casting Process of Cr12MoV Steel
Authors: Wu Guorong , Chen Tianci , Chen Hongyu , Ji Cheng , Zhu Miao‐yong
Published: July 2024

This study identifies optimal cooling rates and critical strain thresholds to prevent cracking in Cr12MoV billets during continuous casting through thermoplastic experiments, high‐temperature tensile tests, and a thermal–mechanical coupled simulation model. The result shows that the critical strain (dimensionless) for corner crack propagation at temperatures of 750, 800, and 850 °C are determined to be 0.125, 0.132, and 0.147, respectively. The critical strain for internal crack formation is found to be 0.03. The simulation results indicate that as the billet enters the first straightening roll, the corner strain is 0.035 and the central strain is 0.025. Upon exiting the fourth straightening roll, the corner strain increases to 0.038, while the central strain decreases to 0.021. Through simulation and high‐temperature confocal in situ observation, it can be concluded that a surface cooling rate of ≥5 °C s−1 effectively prevents cracks during the bending and straightening stage of continuous casting.
Construction of an intranasal drug delivery system with hypothalamus‐targeting nanoparticles
Authors: Rao Qianru , Xu Yujie , Wang Xiaorong , Luo Hang , Li Haoqi , Xiong Jingyuan , Gao Huile , Cheng Guo
Published: July 2024

Dysfunction of the hypothalamus is associated with endocrine imbalances, growth abnormalities, and reproductive disorders. However, there is a lack of targeted treatment strategies focused on the hypothalamus. In this study, we constructed a multifunctional nanocarrier system (S@ANP) to directly target the hypothalamic neurokinin receptor 3 (NK3R) via an intranasal delivery strategy. This system could overcome the primary obstacles in drug delivery for hypothalamus‐related diseases. Under the guidance of a modified (Trp7, β‐Ala8)‐neurokinin A (4‐10) peptide with cysteine, nanoparticles encapsulated with SB222200, an NK3R inhibitor, were found to readily penetrate hypothalamic cells with substantial loading capacity, encapsulation efficiency, and sustained release in vitro. Moreover, intranasal delivery represents an optimal delivery strategy that allows for a significant reduction in oral dosage and enables nanoparticles to bypass the blood‒brain barrier and target relevant parts of the brain. The mucolytic agent N‐acetyl‐L‐cysteine (NAC) was loaded into the nanoparticles (S@ANP + NAC) to increase mucosal solubility and intranasal delivery efficiency. In vivo evaluations showed that S@ANP + NAC could effectively target the hypothalamus and modulate NK3R‐regulated hypothalamic functions in mice. Due to its high hypothalamic targeting efficiency and low toxicity, this intranasal nanoparticle drug delivery system may serve as a potential strategy for precision therapy of hypothalamic disorders.
Impact of surgical specialization on emergency upper gastrointestinal surgery outcomes: A systematic review and meta‐analysis
Authors: Barbaro Antonio , Bunjo Zachary , Asokan Gayatri , Kanhere Akshay , Kuan Li Lian , Trochsler Markus , Kanhere Harsh , Maddern Guy J.
Published: July 2024

Background

Emergency presentations make up a large proportion of a general surgeon's workload. Patients who have emergency surgery carry a higher rate of mortality and complications. We aim to review the impact of surgical subspecialization on patients following upper gastrointestinal (UGI) emergency surgery.

Methods

A systematic search of Ovid Embase, Ovid MEDLINE, and Cochrane databases using a predefined search strategy was completed reviewing studies published from 1st of January 1990 to August 27, 2023. The study was prospectively registered with PROSPERO (CRD42022359326). Studies were reviewed for the following outcomes: 30‐day mortality, in‐hospital mortality, conversion to open, length of stay, return to theater, and readmission.

Results

Of 5181 studies, 24 articles were selected for full text review. Of these, seven were eligible and included in this study. There was a statistically significant improvement in 30‐day mortality favoring UGI specialists (OR 0.71 [95% CI 0.55–0.92 and p = 0.009]) and in‐hospital mortality (OR 0.29 [95% CI 0.14–0.60 and p = 0009]). There was a high degree of study heterogeneity in 30‐day mortality; however, a low degree of heterogeneity within in‐hospital mortality. There was no statistical significance when considering conversion to open and insufficient data to allow meta‐analysis for return to theater or readmission rates.

Conclusion

In emergency UGI surgery, there was improved 30‐day and in‐hospital mortality for UGI specialists. Therefore, surgeons should consider early involvement of a subspecialist team to improve patient outcomes.
Axial Length Measurement
Authors: Cooke David L.
Published: July 2024

The physical conditions for optical biometry are reviewed, and the difference between conventional axial length measurements and segmented, or sum-of-segments axial length readings explained. Segmented axial length reading may have an advantage over the conventional axial length readings—especially in the extreme range—and examples are given of the difference between the two methods and also between different biometers.
Haag-Streit Biometers: Eyestar 900 and Lenstar 900
Authors: Bütler Thomas
Published: July 2024

The Eyestar 900 features swept-source technology, enabling precise measurement, as well as topographic assessment, of the front and back corneal surface and the anterior chamber, including the lens, as well as imaging of all these structures. It also includes cornea-to-retina biometry of the entire eye. The Eyestar 900 uses the Mandala Scan technology with OCT motion compensation, independent of any video-based eye-tracking. The system provides OCT biometry of the entire eye, OCT topography, Zernike analysis with vision simulation, and a reflective dual-zone keratometry. The Lenstar optical biometer features laser interferometry biometry of the entire eye from the cornea to the retina with measurements of all the segments of the human eye, including the corneal thickness, anterior chamber depth, lens thickness, and axial length.
GALILEI G6 Lens Professional
Authors: Schmid Gregor
Published: July 2024

The Galilei G6 is an anterior segment tomographer/topographer based on Scheimpglug and Placido technologies. Additionally, optical biometry is performed with a partial coherence interferometer. A robust anterior corneal topography is obtained merging reflection data from the Placido disk and elevation data from two Scheimpflug cameras. This double camera setup corrects any decentration error improving the accuracy of the measurements which have been proved to be highly accurate and repeatable. Beyond this measuring capability, IOL power calculation benefits from the inclusion of relevant parameters like ray-traced total corneal power and segmental axial length. Several last-generation calculation formulas complete the equipment of this powerful device.
IOL Power Calculations with ORA Intraoperative Aberrometer
Authors: Padrick Tom
Published: July 2024

The ORA system is based on intraoperative aberrometry, a technique developed to calculate the IOL power of the aphakic eye during cataract surgery. A Talbot-Moiré aberrometer, whose details are explained in this chapter, is contained in an optical head mounted to the surgical microscope. After each surgery, the preoperative and surgical data are uploaded to the server and saved in the AnalyzOR database, which is used for optimization of lens constants and for development of improved IOL power calculations and optimization methods. The method used to calculate the power of spherical and toric IOLs and the clinical use in the operating room are described in detail. The results of clinical studies in virgin and in post-refractive surgery eyes are reported.
Hill-RBF: Improving IOL Power Selection by Artificial Intelligence
Authors: Hill Warren E. , Haehnle Jonas
Published: July 2024

The Hill-RBF method is an artificial intelligence model-based approach designed to calculate intraocular lens (IOL) power. The calculation algorithm is completely data-driven and therefore avoids any bias introduced by measurements in a theoretical optics-based method. A selection process identified the best-predicting variables for the model: axial length, mean keratometry, anterior chamber depth, postoperative spherical equivalent and the implanted IOL power. Mathematical boundaries for a 90% precision of ±0.50 D have been defined and cases out-of-bounds are identified. The current version 3.0. has shown a weighted ±0.50 D accuracy of 91.2% with a very few cases out-of-bounds even in unusual eyes.
Hoffer Formulas
Authors: Hoffer Kenneth J.
Published: July 2024

This chapter describes the evolution of the first IOL power calculation formula developed in the United States, through its upgrading over the years as new information developed regarding the biometric relationship involved in calculating the power. It shows the progression right up to the modern incorporation of artificial intelligence into the latest Hoffer QST formula and its free website for calculations.
Pseudophakic Eye Models
Authors: Ribeiro Filomena , Ceia Pedro , Jud Leonor
Published: July 2024

Modeling (statistically, computationally, or physically) the anatomy and optics of the human eye can contribute to assess visual quality, incorporating all known relevant optical phenomena and addressing the developments in intraocular lenses (IOLs) and their corrective capabilities. Throughout this chapter, we describe the abilities and uses of different types of pseudophakic eye models. As a demonstration of their development and applicability to the improvement of the predictive capacity of visual outcomes of cataract surgery, the research carried out by our working group will be described.
The VRF and VRF-G Formulas
Authors: Voytsekhivskyy Oleksiy V.
Published: July 2024

The VRF formula is a vergence-based thin-lens formula using the optical CACD constant and four variables to calculate the IOL power: axial length, keratometry, anterior chamber depth, and horizontal corneal diameter. The VRF-G (where G stands for gender) is an evolution of the VRF that is based on theoretical optics with regression and ray-tracing components. It uses the optical A-constant for the SRK/T formula and operates eight variables including axial length, keratometry, anterior chamber depth, lens thickness, horizontal corneal diameter, central corneal thickness, preoperative refractive spherical equivalent, and gender. The equations of the VRF formula and the published results of both formulas are reported.
Data Analysis in IOL Power Calculations
Authors: Savini Giacomo , Hoffer Kenneth J.
Published: July 2024

This chapters describe the guidelines for studies on IOL power calculation. Information about sample size, timing of postoperative refraction measurement, constant optimization, prediction error and standard deviation calculation, prediction error distribution, mean and median absolute errors, and statistical methods to analyze the refractive outcomes are provided by the authors to the readers.
Toric Calculations
Authors: Savini Giacomo , Abulafia Adi
Published: July 2024

Older toric calculators were limited by the use of the keratometric astigmatism (with no information about posterior corneal curvature) and the adoption of a fixed ratio between the cylinder at the IOL plane and the cylinder at the corneal plane. A discussion about these issues that have been solved by newer calculators is provided along with a brief introduction to the influence of IOL tilt on the refractive outcomes of toric IOLs. The Abulafia-Koch, Barrett, Barrett True-K, EVO, Goggin, Holladay, Johnson & Johnson, Kane, Næser-Savini, Rayner, and Zeiss toric calculators are described. According to the published studies, the percentage of eyes with an absolute prediction error of the cylinder within 0.50 D ranges between 55 and 79% with calculators estimating Total Corneal Astigmatism (TCA), whereas it is close to 40% with calculators using measured TCA and around 25–30% with calculators using Keratometric Astigmatism (KA).
IOL Power Calculation in Keratoplasty
Authors: Borasio Edmondo
Published: July 2024

Accurate IOL power calculation in eyes undergoing simultaneous cataract surgery and corneal transplantation is not possible. Most difficulties arise as a consequence of the unpredictable changes in the anterior and posterior corneal curvature and in their ratio. The keratometry values should ideally be taken from individual case series done with a similar surgical technique (similar corneal graft type; surgical and suturing technique; donor-host cornea size disparity) and always aiming for a mild residual myopia. In endothelial transplants, a myopic refraction of at least -0.75 D should be targeted, due to the expected postoperative hyperopic shift.

Residual refractive errors can be well managed by means of glasses/contact lenses or laser refractive surgery (such as PRK + Mitomycin C or LASIK) and in extreme cases, by means of IOL exchange or piggyback IOL implantation using the refractive vergence formula or raytracing.
Demographics of Biometry
Authors: Melles Ronald B.
Published: July 2024

This is a complete analysis of the demographics of the biometry measurements of the human eye (using optical biometry) based on a very large series of over 80,000 eyes including all races and ages. It is an important update to the first such series of 7500 eyes by Hoffer (using immersion A-scan) more than 40 years ago. There are differences between the sexes (males have longer axial lengths and flatter corneas than females) and among racial groups (Asians have longer axial lengths). These data are important in regard to IOL power calculation and toric IOL implantation.
Soft ionization mechanisms in flexible µ-tube plasma—from FµTP to closed µ-tube plasma
Authors: Speicher Luisa , Song Hao , Ahlmann Norman , Foest Daniel , Höving Simon , Brandt Sebastian , Niu Guanghui , Franzke Joachim , Tian Caiyan
Published: July 2024

In order to find an explanation for the mechanism in a plasma operated with an alternating voltage, or rather a square wave voltage, such a plasma was investigated. It was found that Penning ionization, charge transfer, and photoionization played a minor or even no role in the soft ionization mechanism of a FµTP. If the collision of plasma gases with air does not contribute to soft ionization, it should also be possible to use a separated plasma for soft ionization. Preliminary investigations show that it is possible to ignite a diagnosis gas with a plasma gas even when there is a barrier such as glass between those gases. A temporally and locally limited potential must be produced at the outer surface to achieve this. This potential should be sufficient to ionize the environment softly and to be able to use this so-called closed µ-tube plasma as a new ionization source.
Deep learning-based image quality assessment: impact on detection accuracy of prostate cancer extraprostatic extension on MRI
Authors: Lin Yue , Belue Mason J. , Yilmaz Enis C. , Law Yan Mee , Merriman Katie M. , Phelps Tim E. , Gelikman David G. , Ozyoruk Kutsev B. , Lay Nathan S. , Merino Maria J. , Wood Bradford J. , Gurram Sandeep , Choyke Peter L. , Harmon Stephanie A. , Pinto Peter A. , Turkbey Baris
Published: July 2024

Objective

To assess impact of image quality on prostate cancer extraprostatic extension (EPE) detection on MRI using a deep learning-based AI algorithm.

Materials and methods

This retrospective, single institution study included patients who were imaged with mpMRI and subsequently underwent radical prostatectomy from June 2007 to August 2022. One genitourinary radiologist prospectively evaluated each patient using the NCI EPE grading system. Each T2WI was classified as low- or high-quality by a previously developed AI algorithm. Fisher’s exact tests were performed to compare EPE detection metrics between low- and high-quality images. Univariable and multivariable analyses were conducted to assess the predictive value of image quality for pathological EPE.

Results

A total of 773 consecutive patients (median age 61 [IQR 56–67] years) were evaluated. At radical prostatectomy, 23% (180/773) of patients had EPE at pathology, and 41% (131/318) of positive EPE calls on mpMRI were confirmed to have EPE. The AI algorithm classified 36% (280/773) of T2WIs as low-quality and 64% (493/773) as high-quality. For EPE grade ≥ 1, high-quality T2WI significantly improved specificity for EPE detection (72% [95% CI 67–76%] vs. 63% [95% CI 56–69%], P = 0.03), but did not significantly affect sensitivity (72% [95% CI 62–80%] vs. 75% [95% CI 63–85%]), positive predictive value (44% [95% CI 39–49%] vs. 38% [95% CI 32–43%]), or negative predictive value (89% [95% CI 86–92%] vs. 89% [95% CI 85–93%]). Sensitivity, specificity, PPV, and NPV for EPE grades ≥ 2 and ≥ 3 did not show significant differences attributable to imaging quality. For NCI EPE grade 1, high-quality images (OR 3.05, 95% CI 1.54–5.86; P < 0.001) demonstrated a stronger association with pathologic EPE than low-quality images (OR 1.76, 95% CI 0.63–4.24; P = 0.24).

Conclusion

Our study successfully employed a deep learning-based AI algorithm to classify image quality of prostate MRI and demonstrated that better quality T2WI was associated with more accurate prediction of EPE at final pathology.
Adsorption and desorption of hydroxychloroquine onto sulphur doped graphene powders as a potential drug for COVID-19: physicochemical investigation, surface chemistry and in vitro cytotoxicity evaluation
Authors: Acar Tayfun , Arvas Melih Besir , Arvas Busra , Ucar Burcu , Sahin Yucel
Published: July 2024

Hydroxychloroquine (HCQ) is a very substantial drug active substance that was approved for emergency use by the FDA during the peak of the COVID-19 pandemic due to its potent antiviral properties. In this study, adsorption and desorption of hydroxychloroquine on sulfur (S)-doped graphene powders were investigated. While the adsorption experiments were carried out in the environment of distilled water (pH 5.0-6.0), HEPES buffer (pH 7.6), and Tris.HCl buffer (pH 8.0) the desorption studies were performed in distilled water. The HCQ adsorbed S-doped graphene powders were characterized by UV-Vis, FT-IR, XRD, BET and TEM techniques. According to UV-Vis measurements, the adsorption efficiency in the HEPES buffer medium at pH 7.6 was the highest (68.72% for H3 (HCQ adsorption with SGr3 graphene in HEPES medium)). FT-IR and XRD analyses confirmed the presence of HCQ on the graphene powders’ surface. While morphological changes on the surfaces of graphene powders were imaged by TEM, BET surface area changes proved the HCQ adsorption. The in vitro toxicity of the developed H3 was found to be lower than that of HCQ alone on the L929 cell line. These fundamental findings of the surface interaction between HCQ and graphene are precious for the design and optimization of a targeted drug based on this molecule and material. The adsorption/desorption features of HCQ onto graphene-based carrier systems which in particular doped with sulfur from functional metals have been investigated for the first time.
Pinball-Huber boosted extreme learning machine regression: a multiobjective approach to accurate power load forecasting
Authors: Yang Yang , Lou Hao , Wang Zijin , Wu Jinran
Published: July 2024

Power load data frequently display outliers and an uneven distribution of noise. To tackle this issue, we present a forecasting model based on an improved extreme learning machine (ELM). Specifically, we introduce the novel Pinball-Huber robust loss function as the objective function in training. The loss function enhances the precision by assigning distinct penalties to errors based on their directions. We employ a genetic algorithm, combined with a swift nondominated sorting technique, for multiobjective optimization in the ELM-Pinball-Huber context. This method simultaneously reduces training errors while streamlining model structure. We practically apply the integrated model to forecast power load data in Taixing City, which is situated in the southern part of Jiangsu Province. The empirical findings confirm the method’s effectiveness.
Targeted delivery of FAK siRNA by engineered exosomes to reverse cetuximab resistance via activating paraptosis in colon cancer
Authors: Geng Yiting , Xia Wei , Zheng Xiao , Chen Lujun , Zhou You , Feng Jun , Yuan Ye , Zhang Mingyue , Lu Jianwen , Wei Shanshan , Hu Wenwei
Published: July 2024

Background

Cetuximab is extensively used in the treatment of metastatic colorectal cancer (mCRC). However, resistance poses a significant challenge to successful therapy. Recently, paraptosis, a non-classical programmed cell death, has garnered increased attention for its potential application value in antitumor treatments. We aimed to identify the essential pathways and signaling molecules involved in paraptosis inhibition and select them as therapeutic targets in cetuximab resistance. Additionally, engineered exosome technology is used as a drug delivery system with both targeted and effector properties.

Results

By comparing the differential expression of paraptosis-related genes between drug-resistant colon cancer cells and sensitive cells, it was observed that the paraptosis level induced by cetuximab was significantly downregulated in drug-resistant cells. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified the focal adhesion kinase (FAK) signaling pathway as a key pathway involved in the suppression of paraptosis. The biological function of FAK in cetuximab-resistant cells was investigated through cell morphology observation, CCK-8 assay, colony formation assay, RT-qPCR, Western Blot, and loss-of-function experiments. The results showed that the FAK signaling pathway was significantly upregulated in cetuximab-resistant colon cancer cells, and siRNA interference targeting FAK could notably inhibit cell proliferation while upregulating the paraptosis level. Based on this, engineered colon cancer cells targeted and FAK siRNA loaded exosomes (CT-Exo-siFAK1) were constructed. In vitro experiments, CT-Exo-siFAK1 could effectively activate paraptosis and inhibit the proliferation of drug-resistant colon cancer cells. In vivo experiments also confirmed that CT-Exo-siFAK1 significantly suppressed tumor growth and metastasis while upregulating the paraptosis level.

Conclusion

This study suggests that FAK signaling pathway-mediated inhibition of paraptosis levels is crucial in the sensitivity of cetuximab targeted therapy in colon cancer, and the use of engineered exosomes to deliver FAK siRNA may be an effective strategy to reverse cetuximab resistance.
Energy absorption and resilience in quasi-static loading of foam-formed cellulose fibre materials
Authors: Pääkkönen Elina , Ketoja Jukka A. , Paltakari Jouni
Published: July 2024

To avoid microplastic pollution, there is an urgent need to replace fossil-based cushioning materials in packaging with easily recyclable alternatives. Here, we investigated the potential of lightweight cellulose fibre materials as a solution for mechanical protection. The quasi-static compression was studied among a vast set of 129 different foam-formed trial points with material density ranging from 21 kg/m3 to 123 kg/m3. The trial points included two different fibre types, bleached softwood kraft pulp (BSKP) and bleached chemithermomechanical pulp (CTMP), with varied refining level, pulp consistency, foaming conditions, surfactant type, strength additives, and final material density and thickness. Besides a correlation analysis of factors affecting compression stress and resilience, the results were reflected against a new theoretical prediction of energy absorption for an ideal low-density random fibre network. The theory predicts the initially-high cushion factor to rapidly drop down to the level of 4‒5 at 40‒80% compression. A similar behaviour was seen among the actual samples, despite their various non-ideal features. At 50% compression, the average cushion factor across the whole data set was 4.84 ± 0.10, being close to the theoretical prediction of 4.61 for the ideal case. The smallest cushion factor of 3.6 was found for a CTMP sample. The recovery from compression varied slightly among the samples and appeared highest for the material density of 60‒100 kg/m3, following the predicted proportion of non-buckled fibre segments. According to the results, cellulose fibre-based cushions have a soft initial response, which is preferable for fragile items.

Graphical abstract
Therapeutic Implications and Regulations of Protein Post-translational Modifications in Parkinsons Disease
Authors: Mishra Twinkle , Singh Shareen , Singh Thakur Gurjeet
Published: July 2024

Parkinsons disease (PD) is a neurodegenerative disorder characterized by dopaminergic neuron loss and alpha-synuclein aggregation. This comprehensive review examines the intricate role of post-translational modifications (PTMs) in PD pathogenesis, focusing on DNA methylation, histone modifications, phosphorylation, SUMOylation, and ubiquitination. Targeted PTM modulation, particularly in key proteins like Parkin, DJ1, and PINK1, emerges as a promising therapeutic strategy for mitigating dopaminergic degeneration in PD. Dysregulated PTMs significantly contribute to the accumulation of toxic protein aggregates and dopaminergic neuronal dysfunction observed in PD. Targeting PTMs, including epigenetic strategies, addressing aberrant phosphorylation events, and modulating SUMOylation processes, provides potential avenues for intervention. The ubiquitin–proteasome system, governed by enzymes like Parkin and Nedd4, offers potential targets for clearing misfolded proteins and developing disease-modifying interventions. Compounds like ginkgolic acid, SUMO E1 enzyme inhibitors, and natural compounds like Indole-3-carbinol illustrate the feasibility of modulating PTMs for therapeutic purposes in PD. This review underscores the therapeutic potential of PTM-targeted interventions in modulating PD-related pathways, emphasizing the need for further research in this promising area of Parkinsons disease therapeutics.
Specific sialylation of N-glycans and its novel regulatory mechanism
Authors: Gu Jianguo , Isaji Tomoya
Published: July 2024

Altered glycosylation is a common feature of cancer cells. Some subsets of glycans are found to be frequently enriched on the tumor cell surface and implicated in different tumor phenotypes. Among these, changes in sialylation have long been associated with metastatic cell behaviors such as invasion and enhanced cell survival. Sialylation typically exists in three prominent linkages: α2,3, α2,6, and α2,8, catalyzed by a group of sialyltransferases. The aberrant expression of all three linkages has been related to cancer progression. The increased α2,6 sialylation on N-glycans catalyzed by β-galactoside α2,6 sialyltransferase 1 (ST6Gal1) is frequently observed in many cancers. In contrast, functions of α2,3 sialylation on N-glycans catalyzed by at least three β-galactoside α2,3-sialyltransferases, ST3Gal3, ST3Gal4, and ST3Gal6 remain elusive due to a possibility of compensating for one another. In this minireview, we briefly describe functions of sialylation and recent findings that different α2,3 sialyltransferases specifically modify target proteins, as well as sialylation regulatory mechanisms vis a complex formation among integrin α3β1, Golgi phosphoprotein 3 (GOLPH3), phosphatidylinositol 4-kinase IIα (PI4KIIα), focal adhesion kinase (FAK) and sialyltransferase, which suggests a new concept for the regulation of glycosylation in cell biology.
Waiting for the revolution: how higher education institutions initially responded to ChatGPT
Authors: Korseberg Lene , Elken Mari
Published: July 2024

Although debates regarding the integration of digital technologies in higher education are far from new, the launch of ChatGPT in November 2022 was considered by many as something different from the developments that had come before. This article explores how higher education institutions make sense of the potentiality inherent in artificial intelligence and the early responses to the proliferation of ChatGPT. Through a qualitative interview-based study carried out at three HEIs in Norway, and applying Scott’s (2005) three pillars of institutions as an analytical framework, the article examines the type of change pressure ChatGPT was perceived to represent in the period following its launch and the type of organizational response this perception warranted. The findings show that while it was expected that ChatGPT and related technologies not only could threaten — and potentially challenge — key norms and values in the long run, in the short term it was primarily perceived as a regulatory issue that needed to be controlled by higher education institutions. The article points to an epistemic and temporal imbalance in both the expectations and response to ChatGPT, coupled with a lack of technological competence to fully consider the kind of transformation that artificial intelligence technology potentially represents. Coupled with the sense of artificial intelligence being a “moving target”, this led higher education institutions to an initial state of organizational paralysis, in turn adopting a “wait and see” strategy.
Community-Engaged Data Science (CEDS): A Case Study of Working with Communities to Use Data to Inform Change
Authors: Olvera Ramona G. , Plagens Courtney , Ellison Sylvia , Klingler Kesla , Kuntz Amy K. , Chase Rachel P.
Published: July 2024

Data-informed decision making is a critical goal for many community-based public health research initiatives. However, community partners often encounter challenges when interacting with data. The Community-Engaged Data Science (CEDS) model offers a goal-oriented, iterative guide for communities to collaborate with research data scientists through data ambassadors. This study presents a case study of CEDS applied to research on the opioid epidemic in 18 counties in Ohio as part of the HEALing Communities Study (HCS). Data ambassadors provided a pivotal role in empowering community coalitions to translate data into action using key steps of CEDS which included: data landscapes identifying available data in the community; data action plans from logic models based on community data needs and gaps of data; data collection/sharing agreements; and data systems including portals and dashboards. Throughout the CEDS process, data ambassadors emphasized sustainable data workflows, supporting continued data engagement beyond the HCS. The implementation of CEDS in Ohio underscored the importance of relationship building, timing of implementation, understanding communities’ data preferences, and flexibility when working with communities. Researchers should consider implementing CEDS and integrating a data ambassador in community-based research to enhance community data engagement and drive data-informed interventions to improve public health outcomes.
Capturing Flow Experiences in Everyday Life: A Comparison of Recall and Momentary Measurement
Authors: Bartholomeyczik Karen , Knierim Michael T. , Weinhardt Christof , Oettingen Gabriele , Ebner-Priemer Ulrich
Published: July 2024

In a real-life study using time-based ambulatory assessment, we investigated how to unobtrusively capture within-subject and between-subject variations in flow in everyday life. We compared two observation approaches, momentary states, and coverage, which differed in the reference of flow reports and sampling frequency. Depending on condition, participants (N = 38) answered either ten or five queries per day that referred to the current state or the last two hours (n = 1442 observations in total). We found no effect of either approach on compliance, flow intensity, or flow reports over time. However, the approaches differed with respect to flow probability reports, within-subject variability in flow reports, and perceived burden. In addition, we introduced a reduced three-item version of the Flow Short Scale. Our results indicate acceptable to good reliability as well as concurrent, convergent and discriminant validity of this scale. Based on our findings, we recommend that the choice of observation approach for capturing everyday flow depends on the outcome of interest, the targeted comparison within- or between-subjects, and the expected task variability of the participants. Limitations regarding our sampling procedure and the retrospective assessment of flow experiences are discussed.
On Necessary Optimality Conditions for Sets of Points in Multiobjective Optimization
Authors: Cristofari Andrea , De Santis Marianna , Lucidi Stefano
Published: July 2024

Taking inspiration from what is commonly done in single-objective optimization, most local algorithms proposed for multiobjective optimization extend the classical iterative scalar methods and produce sequences of points able to converge to single efficient points. Recently, a growing number of local algorithms that build sequences of sets has been devised, following the real nature of multiobjective optimization, where the aim is that of approximating the efficient set. This calls for a new analysis of the necessary optimality conditions for multiobjective optimization. We explore conditions for sets of points that share the same features of the necessary optimality conditions for single-objective optimization. On the one hand, from a theoretical point of view, these conditions define properties that are necessarily satisfied by the (weakly) efficient set. On the other hand, from an algorithmic point of view, any set that does not satisfy the proposed conditions can be easily improved by using first-order information on some objective functions. We analyse both the unconstrained and the constrained case, giving some examples.
Radiation sensitivity of biological systems, its modification by chemical modifiers and its quantitative evaluation
Authors: Múčka Viliam , Čuba Václav
Published: July 2024

Large number of sensitizers and protectors of cells, tissues, organs and organisms are being discussed in this review. Attention is paid to metals, nanoparticles or organic compounds as modifiers. They can modify the radiation sensitivity by 20–60%. In most cases, sensitization is caused by an increase in DNA damage or a decrease in the repair of radiation damage. The protection can be caused in many cases by repair of damaged DNA molecules, proteins or enzymes, or by reducing the ROS concentration. The most current research tasks in this area are formulated. A new quantitative and reproducible method of evaluating modifiers is discussed.
Unfairness in AI Anti-Corruption Tools: Main Drivers and Consequences
Authors: Odilla Fernanda
Published: July 2024

This article discusses the potential sources and consequences of unfairness in artificial intelligence (AI) predictive tools used for anti-corruption efforts. Using the examples of three AI-based anti-corruption tools from Brazil—risk estimation of corrupt behaviour in public procurement, among public officials, and of female straw candidates in electoral contests—it illustrates how unfairness can emerge at the infrastructural, individual, and institutional levels. The article draws on interviews with law enforcement officials directly involved in the development of anti-corruption tools, as well as academic and grey literature, including official reports and dissertations on the tools used as examples. Potential sources of unfairness include problematic data, statistical learning issues, the personal values and beliefs of developers and users, and the governance and practices within the organisations in which these tools are created and deployed. The findings suggest that the tools analysed were trained using inputs from past anti-corruption procedures and practices and based on common sense assumptions about corruption, which are not necessarily free from unfair disproportionality and discrimination. In designing the ACTs, the developers did not reflect on the risks of unfairness, nor did they prioritise the use of specific technological solutions to identify and mitigate this type of problem. Although the tools analysed do not make automated decisions and only support human action, their algorithms are not open to external scrutiny.
Technology-Enhanced Collaborative Inquiry in K–12 Classrooms: A Systematic Review of Empirical Studies
Authors: Chen Fan , Chen Gaowei
Published: July 2024

Collaborative inquiry is an instructional approach that encourages student groups to engage in scientific inquiry processes, thereby enhancing their critical thinking and exploratory skills. The effective classroom implementation of this method requires ensuring student engagement in each inquiry stage, where technological tools and activity strategies play a crucial role in supporting their inquiry processes. However, the technological tools and activity strategies that contribute to designing classroom activities and fostering students’ engagement in collaborative inquiry remain unclear. This systematic review analyzed 58 empirical studies on technology-enhanced collaborative inquiry in K–12 classrooms. We examined the characteristics of these studies, the technological tools and activity strategies employed, and their reported outcomes and effects on student learning. The results indicate that most classroom practices featured diverse technological tools and activity strategies to support students in collaboratively performing stages of inquiry tasks. The findings highlight the need for further research into effectively integrating technological tools with activity strategies to provide adaptive support for specific inquiry processes, such as hypothesis generation and scientific argumentation. Our synthesis of previous outcome measurements revealed the positive impacts of technology-enhanced collaborative inquiry on students’ content knowledge, overall inquiry process, and scientific skills like argumentation. The implications of these findings are discussed for both researchers and practitioners, emphasizing the necessity of integrating appropriate technological tools and activity strategies to effectively facilitate collaborative inquiry in K–12 classrooms.
Constructing Social Vulnerability Indexes with Increased Data and Machine Learning Highlight the Importance of Wealth Across Global Contexts
Authors: Zhao Yuan , Paul Ronak , Reid Sean , Coimbra Vieira Carolina , Wolfe Chris , Zhang Yan , Chunara Rumi
Published: July 2024

We consider the availability of new harmonized data sources and novel machine learning methodologies in the construction of a social vulnerability index (SoVI), a multidimensional measure that defines how individuals’ and communities may respond to hazards including natural disasters, economic changes, and global health crises. The factors underpinning social vulnerability—namely, economic status, age, disability, language, ethnicity, and location—are well understood from a theoretical perspective, and existing indices are generally constructed based on specific data chosen to represent these factors. Further, the indices’ construction methods generally assume structured, linear relationships among input variables and may not capture subtle nonlinear patterns more reflective of the multidimensionality of social vulnerability. We compare a procedure which considers an increased number of variables to describe the SoVI factors with existing approaches that choose specific variables based on consensus within the social science community. Reproducing the analysis across eight countries, as well as leveraging deep learning methods which in recent years have been found to be powerful for finding structure in data, demonstrate that wealth-related factors consistently explain the largest variance and are the most common element in social vulnerability.
Integrated multi-view modeling for reliable machine learning-intensive software engineering
Authors: Husen Jati H. , Washizaki Hironori , Runpakprakun Jomphon , Yoshioka Nobukazu , Tun Hnin Thandar , Fukazawa Yoshiaki , Takeuchi Hironori
Published: July 2024

Development of machine learning (ML) systems differs from traditional approaches. The probabilistic nature of ML leads to a more experimentative development approach, which often results in a disparity between the quality of ML models with other aspects such as business, safety, and the overall system architecture. Herein the Multi-view Modeling Framework for ML Systems (M3S) is proposed as a solution to this problem. M3S provides an analysis framework that integrates different views. It is supported by an integrated metamodel to ensure the connection and consistency between different models. To facilitate the experimentative nature of ML training, M3S provides an integrated platform between the modeling environment and the ML training pipeline. M3S is validated through a case study and a controlled experiment. M3S shows promise, but future research needs to confirm its generality.
Singular concepts
Authors: Salmón Nathan
Published: July 2024

Alonzo Church proposed a powerful and elegant theory of sequences of functions and their arguments as surrogates for Russellian singular propositions and singular concepts. Church’s proposed theory accords with his Alternative (0), the strictest of his three competing criteria for strict synonymy. The currently popular objection to strict criteria like (0) on the basis of the Russell–Myhill antinomy is here rebutted. Russell–Myhill is not a problem specifically for Alternative (0); it is a refutation of unrestrained concept comprehension. Unrestricted comprehension is also inconsistent with facts about sets of properties. Criteria more lax than (0) are philosophically inadequate. In particular, the rival conception of propositions as classes of possible worlds is subject to a fatal philosophical collapse. It follows on that conception, given that each of us is fallible, that everyone believes everything. It is shown, however, that Church’s proposed theory is vulnerable under (0) to a version of Russell’s notorious Gray’s Elegy objection. Some amendments to Church’s proposal are proffered, including an amendment, first proposed in the author’s Frege’s Puzzle (1986), that addresses Russell’s objection. Church’s response (personal correspondence) is considered.
Sequential Electrochemical and Chemical Multi-Polymerization of Catechol for Abatement of Environmental Pollutants
Authors: Altıncı Osman Cem , Körbahti Bahadır K.
Published: July 2024

Catechol is a substance that is commonly found in wastewaters from a variety of sectors including paper, paint, petroleum, dyes, antioxidants, pesticides, iron and steel, solvents, nylon, detergent, textile, plastic, rubber, cosmetics, and medicine. In this study, sequential electrochemical and chemical multi-polymerization of catechol was investigated for environmental pollution abatement. The effect of operating parameters like catechol concentration (2–10 g/L), ammonium persulphate (APS) concentration (2–10 g/L) and reaction temperature (20–60 °C) were evaluated using response surface methodology. Catechol concentration was determined using HPLC in a gradient mobile phase. The electrochemical behavior of the polymer was investigated by cyclic voltammetry (CV). The structural and morphological properties of polycatechol were characterized by Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy with energy dispersive X-ray (SEM–EDX) analysis. It was observed from the SEM images a polymeric structure developed from a crystalline and heterogeneous structure when the APS concentration increased. Similarly, it was seen in SEM images that the polymers transitioned from a bulk and heterogeneous structure to a homogeneous structure as the temperature increased, and back to a heterogeneous structure as the catechol concentration increased. It was also found that catechol removal increased and reaction selectivity decreased by increasing the reaction temperature. The optimum operating conditions were found as 4 g/L catechol concentration, 9.5 g/L APS concentration, 30 °C reaction temperature with 100 cycles at 50 mV/s of electrochemical polymerization and 72 h of chemical polymerization. The results of this study show the potential of challenging new routes not only facile polymerization of organic monomers but also to decrease the undesirable pollutant concentration in the wastewater.
Transcriptomic Differences in Medullary Thyroid Carcinoma According to Grade
Authors: Ruz-Caracuel Ignacio , Caniego-Casas Tamara , Alonso-Gordoa Teresa , Carretero-Barrio Irene , Ariño-Palao Carmen , Santón Almudena , Rosas Marta , Pian Héctor , Molina-Cerrillo Javier , Luengo Patricia , Palacios José
Published: July 2024

Medullary thyroid carcinoma (MTC) is a rare cancer derived from neuroendocrine C-cells of the thyroid. In contrast to other neuroendocrine tumors, a histological grading system was lacking until recently. A novel two-tier grading system based on the presence of high proliferation or necrosis is associated with prognosis. Transcriptomic analysis was conducted on 21 MTCs, including 9 high-grade tumors, with known mutational status, using the NanoString Tumor Signaling 360 Panel. This analysis, covering 760 genes, revealed upregulation of the genes EGLN3, EXO1, UBE2T, UBE2C, FOXM1, CENPA, DLL3, CCNA2, SOX2, KIF23, and CDCA5 in high-grade MTCs. Major pathways differentially expressed between high-grade and low-grade MTCs were DNA damage repair, p53 signaling, cell cycle, apoptosis, and Myc signaling. Validation through qRT-PCR in 30 MTCs demonstrated upregulation of ASCL1, DLL3, and SOX2 in high-grade MTCs, a gene signature akin to small-cell lung carcinoma, molecular subgroup A. Subsequently, DLL3 expression was validated by immunohistochemistry. MTCs with DLL3 overexpression (defined as ≥ 50% of positive tumor cells) were associated with significantly lower disease-free survival (p = 0.041) and overall survival (p = 0.01). Moreover, MTCs with desmoplasia had a significantly increased expression of DLL3. Our data supports the idea that DLL3 should be further explored as a predictor of aggressive disease and poor outcomes in MTC.
Multiple Roles of Apolipoprotein E4 in Oxidative Lipid Metabolism and Ferroptosis During the Pathogenesis of Alzheimer’s Disease
Authors: Faraji Parisa , Kühn Hartmut , Ahmadian Shahin
Published: July 2024

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease worldwide and has a great socio-economic impact. Modified oxidative lipid metabolism and dysregulated iron homeostasis have been implicated in the pathogenesis of this disorder, but the detailed pathophysiological mechanisms still remain unclear. Apolipoprotein E (APOE) is a lipid-binding protein that occurs in large quantities in human blood plasma, and a polymorphism of the APOE gene locus has been identified as risk factors for AD. The human genome involves three major APOE alleles (APOE2, APOE3, APOE4), which encode for three subtly distinct apolipoprotein E isoforms (APOE2, APOE3, APOE4). The canonic function of these apolipoproteins is lipid transport in blood and brain, but APOE4 allele carriers have a much higher risk for AD. In fact, about 60% of clinically diagnosed AD patients carry at least one APOE4 allele in their genomes. Although the APOE4 protein has been implicated in pathophysiological key processes of AD, such as extracellular beta-amyloid (Aβ) aggregation, mitochondrial dysfunction, neuroinflammation, formation of neurofibrillary tangles, modified oxidative lipid metabolism, and ferroptotic cell death, the underlying molecular mechanisms are still not well understood. As for all mammalian cells, iron plays a crucial role in neuronal functions and dysregulation of iron homeostasis has also been implicated in the pathogenesis of AD. Imbalances in iron homeostasis and impairment of the hydroperoxy lipid-reducing capacity induce cellular dysfunction leading to neuronal ferroptosis. In this review, we summarize the current knowledge on APOE4-related oxidative lipid metabolism and the potential role of ferroptosis in the pathogenesis of AD. Pharmacological interference with these processes might offer innovative strategies for therapeutic interventions.