bluuebunny/crossref_metadata_2025 huggingface dataset:
Temperature‐Dependent Deformation Behavior of 316 Stainless Steel with Heterogeneous Microstructure
Authors: Wan Jiahe , Fu Bin , Guo Yanhui , Pang Linghuan , Li Xiaolin
Published: December 2024

Systematic investigations are conducted to elucidate the temperature‐dependent mechanical properties and deformation behavior of a heterogeneous structured 316 stainless steel, which features a combination of deformed and reversed/recrystallized grains. It is found that the yield strength of the heterogeneous structured specimen is significantly higher at cryogenic temperature compared to room temperature, whereas the yield strength of the uniformly structured specimen remains largely unchanged. This difference is primarily attributed to the strengthening contribution from dislocations and heterogeneous deformation‐induced strengthening in the heterogeneous structured specimen. Additionally, the heterogeneous structured specimen exhibits an impressive elongation of 65.45%, markedly higher than that observed at room temperature. At room temperature, deformation is predominantly driven by dislocation activity. In contrast, under cryogenic condition, the initial stage of deformation is characterized by the plateau due to the transformation‐induced plasticity (TRIP) effect. This is followed by the development of localized shear bands, which induce further TRIP effect. These findings suggest that heterogeneous structured 316 stainless steel is well‐suited for applications requiring both high strength and toughness in low‐temperature environment.
Identification and Quantitation of Signature Constituents of Dant‐Kanti, a Herbo‐Dental Formulation Using UHPLC, HPTLC, and GC–MS, and its Anti‐Inflammatory Effects on Porphyromonas gingivalis Lipopolysaccharide‐Induced Human Macrophages
Authors: Balkrishna Acharya , Maheswari Priya Rani , Varshney Yash , Tomer Meenu , Joshi Monali , Gujral Seema , Dev Rishabh , Srivastava Jyotish , Nain Pardeep , Varshney Anurag
Published: December 2024

A herbo‐dental formulation, Dant‐Kanti natural toothpaste consists of 13 potent medicinal herbs. The present study aims to comprehensively identify the signature phytometabolites present in Dant‐Kanti natural toothpaste using high‐performance thin layer chromatography (HPTLC), ultra‐high‐performance liquid chromatography (UHPLC), and gas chromatography–mass spectrometry (GC–MS) methods. Among the identified phytometabolites, gallic acid, piperine, and anethole, were quantified by UHPLC, whereas camphor, menthol, thymol, and eugenol were quantified using GC–MS. An inductively coupled plasma‐mass spectrometry was used to estimate the mineral contents in Dant‐Kanti natural toothpaste. To the best of our knowledge, these studies are the first‐ever to identify all the signature components in an herbal dental formulation. These developed and validated methodologies were then used across 25 distinct batches of Dant‐Kanti natural toothpaste, in oder to ascertain the consistency and homogeneity. Both the UHPLC, and GC–MS methods used in this study were validated as per ICH Q2 (R1) guidelines, and were found to be suitable, linear (r > 0.99), and precise. In the cell‐biological study, Dant‐Kanti natural toothpaste showed a concentration‐dependent reduction in proinflammatory cytokine release, in human macrophages induced with Porphyromonas gingivalis lipopolysaccharide. This robust study methodology, validation, and results provide valuable insights into the complex composition of Dant‐Kanti natural toothpaste, and contribute to the understanding of its potential oral health benefits.
Increased Expression of MST1 in Patients With Epilepsy and in a Rat Model of Epilepsy
Authors: Xia Di , Zhang Linming , Mei Rong , Wu Chunhua , Liu Yan , Chen Hongyu , Chen Ling
Published: December 2024

Mammalian sterile20‐like kinase 1 (MST1), a serine/threonine kinase frequently expressed, has emerged as pivotal modulator of multiple physiological and pathological conditions such as cellular growth, programmed cell death, oxidative stress, neurodegeneration, inflammation, and synaptic plasticity in the central nervous system. Various neurological diseases are associated with the activation of MST1. Epilepsy is a severe neurological disorder characterized by abrupt abnormal electrical activity in the brain and recurring spontaneous seizures. The most common pathological discoveries in patients and animal models with epilepsy are neuronal death, inflammation, neurodegeneration, neurogenesis, and axonal regrowth. The purpose of this study was to assess the levels of MST1 in serum and cerebrospinal fluid (CSF) specimens obtained from individuals diagnosed with epilepsy. In addition, it aimed to explore the expression pattern of MST1 in brain tissues of epileptic rats. We used enzyme‐linked immunosorbent assay to measure the levels of CSF and serum MST1 in 10 epilepsy patients and 9 control patients. After creation of epilepsy models with healthy male Sprague‐Dawley rats using lithium and pilocarpine, the expression of MST1 in the temporal cortex and hippocampus was evaluated at different time points (6 h, 24 h, 3 days, 7 days, 14 days, and 30 days after seizures) using immunofluorescence, immunohistochemistry, and Western blotting. In patients with epilepsy, the levels of CSF‐MST1 were elevated (593.90 ± 16.28 vs. 560.40 ± 19.42 pg/mL, p < 0.05) compared to the control group. Accordingly, the serum‐MST1 levels were 583.40 ± 19.70 pg/mL in the epilepsy group and 555.70 ± 20.14 pg/mL in the control group, demonstrating a statistically significant distinction (p < 0.05). Levels of MST1 in CSF and serum could be of diagnostic help. Neuronal apoptosis in temporal cortex and hippocampus of epileptic rats was detected using terminal deoxynucleotidyl transferase dUTP nick end labeling staining. MST1 was expressed in the neuronal membrane and cytoplasm of the temporal cortex and hippocampus. The expression of MST1 increased after seizures, showing a relatively high level within 30 days and reaching its highest point on the seventh day after status epilepticus. The findings of this study indicate that the increased expression of MST1 protein in patients with epilepsy and epileptic rats might play a role in the development of epilepsy.
Ontogeny of foraging behaviour in an opportunistic gull inhabiting urban marine ecosystems
Authors: Navarro Joan , Martín-Vélez Víctor , Giménez Joan , Antonio Garcia José , Cermeño Pablo , Figuerola Jordi , Aymí Raül , Montalvo Tomás
Published: December 2024

Urbanization affects ecosystems by reducing biodiversity and displacing species from native habitats. While some suffer, others, like urban wildlife, adapt through innovative feeding and behaviours that improve their fitness in human‐altered settings. Despite research on wildlife in urban areas, the development of foraging behaviour in urban species is still understudied. Here, we examined the age‐related differences in the foraging behaviour of yellow‐legged gulls Larus michahellis in Barcelona (Spain), a densely populated coastal urban ecosystem. Using biologging technologies and trophic markers, we compared the foraging strategies, habitat use, human interactions, and trophic niches of juvenile, immature, and adult yellow‐legged gulls over three breeding seasons. The results showed age‐related differences in spatial distribution and foraging behaviour in this opportunistic species. Juveniles and immatures mainly foraged in ports and at sea, while adults favoured urban habitats. These patterns likely stem from reproductive constraints in adults and lower foraging efficiency in younger birds. Adults' primary use of urban habitats also explains their higher trophic niche. Furthermore, fishing activity significantly influenced yellow‐legged gull foraging across age groups, with strong associations between gulls and fishing vessels. By studying how age and life stage influence habitat use and behaviour, this research provides insights to guide targeted management strategies for this species.
Introduction to Cognitive Economics
Authors: Caplin Andrew
Published: December 2024

This chapter introduces cognitive economics. It explains its inter-disciplinary nature and the fundamental role of utility functions, subjective beliefs, costs of learning, and Blackwell experiments. It outlines the need for economic data engineering to separate out beliefs from preferences and thereby to scientifically study decision-making mistakes. It also discusses distinctions and connections between cognitive economics and behavioral economics.
Cognitive Capital and Human-AI Interactions
Authors: Caplin Andrew
Published: December 2024

This chapter introduces cognitive capital and human-AI interactions. The upcoming cognitive revolution, like its industrial precursor, is defined by a radical change in technology. The machines of today introduce intangible cognitive capital that substitutes for human mental effort. The chapter lays out a three stage human-AI decision-making pipeline. This starts with human labeling of cases, continues with minimization of the AI loss function, and involves a final stage of human-AI collaboration. The chapter introduces outlines a field study in which elicited beliefs improve labeling for cancer detection. It introduces recent findings showing that standard engineering methods of defining loss functions can fail in their own terms. As a result, there is a bilateral alignment problem that requires not only that the AI is trained in human preferences, but that humans understand the AI's costs and constraints.
Cognitive Economics Takes Off
Authors: Caplin Andrew
Published: December 2024

This chapter presents a history of cognitive economics framed in terms of Walt Rostow’s stages of economic growth. It highlights the important early contribution of Paul Samuelson, who introduced revealed preference theory, as well as that of Henry Block and Jacob Marschak, who were the first to propose measure¬ment of new basic observations to separate preferences from beliefs. It outlines ongoing research on rational inattention, bounded rationality, efficient coding, salience-based attention, imperfect memory, resource rationality, and cognitive hierarchies. It discusses important new forms of measurement that are advancing the research frontier in cognitive economics, including economic surveys, process measures, and state dependent stochastic choice data. It outlines the broader convergence of interest between psychologists and economists on the importance of cognitive constraints.
The Contingencies of Understanding
Authors: Prior Christopher , Higgins Joseph
Published: December 2024

We consider the processes by which Frank Oates acquired understanding of the peoples with whom he came into contact in southern Africa in the early 1870s, and the Ndebele people in particular. We place emphasis on the importance of ‘intermediaries’, individuals Oates judged not of a place but nevertheless considered experts in it, in shaping the traveller’s macro understandings of the region. We consider the role of social consonance in explaining the alacrity with which Oates accepted ways of reading Africa from some and not others. We also consider the processes by which Oates developed understandings of the flora and fauna of the region, and African guides’ roles in this. We evaluate the impact of factors such as race and gender on the recordings of the colonial encounter, and the areas in which Oates did and did not change his understandings over time. In our emphasis upon the importance of intermediaries, we explore the fragilities and contingencies that lay behind the development of European understandings of pre-colonial Africa.
Introduction
Authors: Qu Xue , Kojima Daizo , Wu Laping , Ando Mitsuyoshi
Published: December 2024

With a large and growing population, ensuring an adequate food supply has always been one of the most important goals worldwide.
The Effect of Outsourcing Service on Rice Harvest Loss Through Moral Hazard
Authors: Qu Xue , Kojima Daizo , Wu Laping , Ando Mitsuyoshi
Published: December 2024

In Chap. 4, we compare the work attitudes of service providers and farmers to study the moral hazards of service providers and find that service providers’ work attitude is less serious than that of farmers. In this chapter, we will study whether the negative effect of harvest outsourcing services on operators’ work attitudes will lead to increased rice harvest losses.
The Effect of Moral Hazard on Rice Harvest Loss
Authors: Qu Xue , Kojima Daizo , Wu Laping , Ando Mitsuyoshi
Published: December 2024

In Chap. 5, the mediation path that the negative effect of harvest outsourcing services on operators’ work attitudes will lead to increased rice harvest losses is examined through mediation analysis models. In the previous chapters, the effect of service providers’ moral hazards on rice harvest losses has not been studied directly. In this chapter, we focus only on farmers using harvest outsourcing services and directly explore the effect of service providers’ moral hazards on rice harvest losses.
Three-dimensional spatial localization and volume estimation of prostate tumors using 18F-PSMA-1007 PET/CT versus multiparametric MRI
Authors: Huang Guocheng , Albers Patrick , Mookerji Nikhile , Pfanner Tyler , Hui Amaris , Mittal Rohan , Broomfield Stacey , Dean Lucas , St. Martin Blair , Jacobsen Niels-Erik , Evans Howard , Gao Yuan , Hung Ryan , Abele Jonathan , Dromparis Peter , Lima Joema Felipe , Bismar Tarek A. , Michelakis Evangelos , Sutendra Gopinath , Wuest Frank , Tu Wendy , Adam Benjamin A. , Fung Christopher , Ghosh Sunita , Tamm Alexander , Kinnaird Adam ,   The Next Generation Trial Investigators, Huang Guocheng , Albers Patrick , Mookerji Nikhile , Pfanner Tyler , Hui Amaris , Mittal Rohan , Broomfield Stacey , Dean Lucas , St. Martin Blair , Jacobsen Niels-Erik , Evans Howard , Gao Yuan , Hung Ryan , Abele Jonathan , Dromparis Peter , Lima Joema Felipe , Bismar Tarek A. , Michelakis Evangelos , Sutendra Gopinath , Wuest Frank , Tu Wendy , Adam Benjamin A. , Fung Christopher , Ghosh Sunita , Tamm Alexander , Kinnaird Adam
Published: December 2024

Purpose

Fluorine-18 prostate-specific membrane antigen-1007 positron emission tomography/computed tomography (18F-PSMA-1007 PET/CT) has been shown to be superior to multiparametric magnetic resonance imaging (MRI) for the locoregional staging of intermediate-risk and high-risk prostate tumors. This study aims to evaluate whether it is also superior in estimating tumor parameters, such as three-dimensional spatial localization and volume.

Methods

134 participants underwent 18F-PSMA-1007 PET/CT and MRI prior to radical prostatectomy as part of the validating paired-cohort Next Generation Trial (NCT05141760). MRI, 18F-PSMA-1007 PET/CT, and final pathology were independently assessed by blinded radiologists, nuclear medicine physicians, and pathologists, respectively. Individual tumor nodules were measured in three dimensions and cognitively registered to 38 segment prostate diagrams as per PI-RADSv2.1. Correct spatial localization was compared using McNemar test and estimation of tumor volumes were compared using linear regression and partial F-test.

Results

286 tumor nodules were identified by final histopathology. 18F-PSMA-1007 PET/CT was superior to MRI for correct localization (186 [65.0%] vs 134 [46.9%], p < 0.001) and tumor volume estimation (R2 = 0.545 vs 0.431, p < 0.001). Larger tumors and higher Gleason Grade Group (GGG) were associated with correct localization by 18F-PSMA-1007 PET/CT (OR = 2.05, p < 0.001 for tumor volume and OR = 4.92, p < 0.01 for ≥ GGG3) and MRI (OR = 1.81, p < 0.001 for tumor volume and OR = 11.67, p < 0.001 for ≥ GGG3).

Conclusion

18F-PSMA-1007 PET/CT outperforms MRI for determination of three-dimensional spatial localization and volume of prostate tumors. These findings support the use of 18F-PSMA-1007 PET/CT prior to definitive treatment of localized prostate cancers.
Physician vs. AI-generated messages in urology: evaluation of accuracy, completeness, and preference by patients and physicians
Authors: Robinson Eric J. , Qiu Chunyuan , Sands Stuart , Khan Mohammad , Vora Shivang , Oshima Kenichiro , Nguyen Khang , DiFronzo L. Andrew , Rhew David , Feng Mark I.
Published: December 2024

Purpose

To evaluate the accuracy, comprehensiveness, empathetic tone, and patient preference for AI and urologist responses to patient messages concerning common BPH questions across phases of care.

Methods

Cross-sectional study evaluating responses to 20 BPH-related questions generated by 2 AI chatbots and 4 urologists in a simulated clinical messaging environment without direct patient interaction. Accuracy, completeness, and empathetic tone of responses assessed by experts using Likert scales, and preferences and perceptions of authorship (chatbot vs. human) rated by non-medical evaluators.

Results

Five non-medical volunteers independently evaluated, ranked, and inferred the source for 120 responses (n = 600 total). For volunteer evaluations, the mean (SD) score of chatbots, 3.0 (1.4) (moderately empathetic) was significantly higher than urologists, 2.1 (1.1) (slightly empathetic) (p < 0.001); mean (SD) and preference ranking for chatbots, 2.6 (1.6), was significantly higher than urologist ranking, 3.9 (1.6) (p < 0.001). Two subject matter experts (SMEs) independently evaluated 120 responses each (answers to 20 questions from 4 urologist and 2 chatbots, n = 240 total). For SME evaluations, mean (SD) accuracy score for chatbots was 4.5 (1.1) (nearly all correct) and not significantly different than urologists, 4.6 (1.2). The mean (SD) completeness score for chatbots was 2.4 (0.8) (comprehensive), significantly higher than urologists, 1.6 (0.6) (adequate) (p < 0.001).

Conclusion

Answers to patient BPH messages generated by chatbots were evaluated by experts as equally accurate and more complete than urologist answers. Non-medical volunteers preferred chatbot-generated messages and considered them more empathetic compared to answers generated by urologists.
Enhanced recovery protocol for congenital duodenal obstruction – initial experiences with development and implementation
Authors: Røkkum Henrik , Treider Martin Alavi , Børke Wenche Bakken , Bergersen Janicke , Lassen Kristoffer , Støen Ragnhild , Sæter Thorstein , Bjørnland Kristin
Published: December 2024

Background

The experience with Enhanced Recovery After Surgery® (ERAS®) protocols in neonatal intestinal surgery is very limited. We present the development and implementation of an Enhanced Recovery Protocol (ERP) designed specifically for neonates treated for congenital duodenal obstruction (CDO), and early outcome after implementation.

Methods

An ERP for CDO was developed and implemented. Experiences with ERP development and implementation are described. Early clinical outcome in patients treated before (January 2015–Descember 2020) and after (February 2022–September 2024) implementation were compared. Ethical approval was obtained.

Results

A multidisciplinary ERP team was established. The ERP for CDO was developed with stakeholder involvement. Implementation was challenging, but with close follow-up and frequent meetings with the involved medical disciplines, an overall ERP compliance of 80% was achieved for the 21 patients treated after implementation. Compared to 40 patients treated before ERP implementation (January 2015-Descember 2020), the use of minimally invasive surgery increased and time to first postoperative enteral and breast feed were reduced, without increasing the rate of postoperative complications.

Conclusions

This study presents an ERP specifically designed for CDO with a unique description of our experiences with the development and implementation process. Early results suggest that this ERP for CDO is feasible and safe.
Comparing functional outcomes between 3D printed acetabular cups and traditional prosthetic implants in hip arthroplasty: a systematic review and meta analysis
Authors: St. John Ryan , Spicer Seth , Hadaya Mo , Brancaccio Hanna , Park Seungkyu , McMillan Sean
Published: December 2024

Objective

The primary research aim was to determine if the use of traditional or 3D printed prosthesis resulted in better functional outcome scores in hip arthroplasty.

Methods

A systematic review and meta-analysis was conducted utilizing the PRISMA 2020 guidelines. Six databases (PubMed, Embase, Scopus, WebOfScience, and Cochrane Library, Google Scholar) were searched yielding 1117 article titles and abstracts. Rayyan.ai was used to detect duplicates (n = 246) and for manual screening for inclusion and exclusion criteria. Included were controlled studies of any publication time that assessed Harris Hip Score (HHS) at baseline and twelve months. Six papers were sought for full text review of which three studies totaling 195 hips met final inclusion.

Results

Mean HHS in the control group went from 38.15 (± 6.02) at baseline to 80.30 (± 4.79) at twelve months follow-up, while the 3D group saw a change from 37.81 (± 5.84) to 90.60 (± 4.49). Significant and large improvements between time points were seen within the control group [p = .02, Cohen’s d = 8.57 (1.48, 15.56)] and 3D group [p < 0.01, Cohen’s d = 9.18 (3.50, 14.86)]. The HHS score of the 3D group improved by 10.64 points more than the HHS score of the control group, which is a statistically insignificant (p = 0.89) amount.

Conclusion

Group differences in pooled mean HHS scores at twelve months follow-up surpassed established minimum differences for clinical importance. High quality research should be further pursued to elucidate these findings.
An optimized ensemble model based on meta-heuristic algorithms for effective detection and classification of breast tumors
Authors: Saber Abeer , Elbedwehy Samar , Awad Wael A. , Hassan Esraa
Published: December 2024

One of the most common cancers among women worldwide is breast cancer (BC), and early diagnosis can save lives. Early detection of BC increases the likelihood of a successful outcome by enabling treatment to start sooner. Even in areas without access to a specialist physician, machine learning (ML) aids in early BC detection. The medical imaging community is becoming more interested in using ML, and deep learning (DL) to increase the accuracy of cancer screening. Many disease-related data are sparse. However, for DL models to perform well, a large amount of data is required. Because of this, the DL models that are currently in use on medical images are not as effective as they could be. Convolutional neural network (CNN) models have recently gained popularity in the medical industry, and they perform admirably in terms of high performance and robustness at image classification. The proposed method classifies data using ensemble pre-trained models such as the dense convolutional network (DenseNet)-121 and EfficientNet-B5 feature extractor networks, as well as the support vector machine for classification. Using a modified meta-heuristic optimizer, the selected pre-trained CNN hyperparameters were optimized to improve the performance. The experimental results for the presented model on the INbreast dataset show that the EfficientNet-B5 model is effective for BC classification, with overall accuracy, sensitivity, specificity, precision, and area under the ROC curve (AUC) values of 99.9%, 99.9%, 99.8%, 99.1%, 1.0, respectively.
Climate characteristics and trends of extreme daily precipitation events associated with cold fronts in the metropolitan region of São Paulo, Brazil
Authors: Segura Caroline Santos , da Rocha Rosmeri Porfírio , Crespo Natália Machado
Published: December 2024

The metropolitan region of São Paulo (MRSP), located in southeastern Brazil, is densely populated and economically significant for the country. Cold fronts crossing MRSP are crucial for the precipitation regime and can induce extreme rainfall events. Therefore, this study presents a climatology of the contribution of cold fronts to extreme rainfall events in the MRSP and their associated synoptic patterns, using long term (1960 to 2022) local observations to identify cold fronts and daily rainfall extremes, and a time window of 5 days (from 2 days before and after). The mean circulation patterns associated with these events are analyzed using gridded precipitation and reanalysis for a short period (1980–2022). For 1960–2022, a total of 2535 cold fronts and 1077 extremes rainfall events were identified, with 58% of the daily extremes being associated with cold fronts. These events mainly occur during the austral spring, although their daily mean precipitation is higher in the austral summer. The contribution of cold fronts to extreme precipitation exhibits a statistically significant decrease, contrasting with the increasing trend in daily rainfall extremes. This suggests the influence of other meteorological systems in increasing rainfall extremes. The synoptic patterns reveal an intense anticyclone located southwest of the main trough in the lower troposphere, intense cyclonic vorticity along the front at low levels, stronger upper troposphere divergence, and strong thickness gradients in the 500–1000 hPa layer affecting MRSP. Most extremes occur on the day before and the day of the cold front due to more favorable dynamic conditions for convective activity.
Computer-aided design of caffeic acid derivatives: free radical scavenging activity and reaction force
Authors: Morales-García B. Carolina , Pérez-González Adriana , Álvarez-Idaboy J. Raúl , Galano Annia
Published: December 2024

Context

Antioxidants are known to play a beneficial role in human health. Caffeic acid has been previously recognized as efficient in this context. However, such a capability can be enhanced through structural modification. Thus, 3829 caffeic acid derivatives were computational designed to that purpose by adding functional groups (-OH, -SH, -OCH3, -COOCH3, -F, -CF3, and -N(CH3)(C2H5)) to its framework. Promising candidates were chosen considering drug-like behavior, toxicity, and synthetic accessibility. The best candidates, dCAF-2, dCAF-16, and dCAF-82, were identified by comparison with reference antioxidants. The thermochemistry and kinetics of their reaction with •OOH are provided. The global rate coefficients were estimated to be 1.76 × 109 M−1 s−1, 3.19 × 109 M−1 s−1, and 1.79 × 109 M−1 s−1 in aqueous solution for dCAF-2, dCAF-16, and dCAF-82, respectively. In lipid medium, their total rate coefficients were estimated to be 3.65 × 103 M−1 s−1, 3.73 × 103 M−1 s−1, and 8.63 × 104 M−1 s−1 for dCAF-2, dCAF-16, and dCAF-82, respectively. These values allow predicting the designed caffeic acid derivatives as excellent antioxidants in both environments. The reaction forces for the main reaction path of the dCAF-2, dCAF-16, and dCAF-82 reactions with •OOH were explored.

Methods

Three protocols were used: (i) CADMA-Chem (computer-assisted design of multifunctional antioxidants, based on chemical properties) to quantify ADME (absorption, distribution, metabolism, and excretion) properties, toxicity and synthetic accessibility; (ii) eH-DAMA (electron and hydrogen donating ability map) tool, to identify the derivatives expected to behave as the best antioxidants; (iii) QM-ORSA (quantum mechanics–based test for overall free radical scavenging activity), to calculate the rate constants. Electronic structure calculations were performed with Gaussian 09, at the M05-2X/6–311 + g(d,p) level of theory. Both aqueous and lipid environments were considered using the SMD continuous solvation model. Intrinsic reaction coordinate (IRC) calculations, as implemented in Gaussian 09, were used to obtain the reaction force.
How are patient inputs considered in HTA? A thematic document analysis of NICE ultra-rare disease appraisals
Authors: Gentilini Arianna , Rana Alina
Published: December 2024

Patient organisations are increasingly involved in HTA. Given this, it is important to understand what these organisations contribute and how their voices are accounted for in the decision-making process. This study characterises inputs from patient organisations and/or their nominated patient experts in technology appraisals for ultra-rare diseases in England and Wales and seeks to understand how these are considered in NICE final recommendations. We thematically analysed all HST appraisals completed between January 2022 and August 2024 (N = 15). We appraised inputs from patient organisations’ and experts’ written submissions, the novelty of patient inputs, as well as financial ties between contributing organisations and the manufacturer of the technology being appraised. We compared themes identified with those found in the Final Evaluation Determination documents to understand how and to what extent patients’ inputs were considered in NICE final recommendations. We found that patient submissions mainly focused on disease aspects (54%). Patients raised concerns on access challenges, caregiver burden, and mental health impacts. Most patient themes overlapped with manufacturers’ submissions (82%) and doctors’ testimonies (45%), with most novel insights focusing on access issues and mental health. Patient organisations reported receiving funding from the technology manufacturer in most appraisals, with amounts ranging from £5,000 to £74,113. Approximately half of patient inputs were explicitly mentioned in NICE final decision documents, with some considerations being neglected despite being raised by patients. While NICE incorporates many issues of importance to patients, there is room for improvement to ensure all aspects patients deem important are captured. Further research could pinpoint optimal areas for patient contributions and assess their impact.
Multinational platforms and legitimacy spillovers
Authors: Li Sali , Stallkamp Maximilian , Shaheer Noman , Chen Liang
Published: December 2024

Multinational platforms (MNPs), such as TikTok, Grab, and Airbnb, are facing significant legitimacy challenges in foreign markets. While some of these challenges are similar to those experienced by conventional multinational enterprises (MNEs), the platform-based business models of MNPs, which create value primarily through networks of external users and complementors, rather than through hierarchically controlled foreign subsidiaries, lead to unique legitimacy challenges and open up novel strategies for overcoming them. We explore how MNPs can leverage legitimacy spillovers from their complementors to overcome legitimacy challenges and establish credibility in new markets. We propose that effective governance and strategic management of complementor relationships can significantly enhance MNPs’ legitimacy across diverse institutional contexts. Our findings contribute to the literature on digital platform internationalization, offering new insights and strategic tools for MNP managers to navigate the complex global landscape.
On the convergence of generalized kernel-based interpolation by greedy data selection algorithms
Authors: Albrecht Kristof , Iske Armin
Published: December 2024

We analyze the convergence of generalized kernel-based interpolation methods. This is done under minimalistic assumptions on both the kernel and the target function. On these grounds, we further prove convergence of popular greedy data selection algorithms for totally bounded sets of sampling functionals. Supporting numerical results concerning computerized tomography are provided for illustration.
Wi-Fi signal for soil moisture sensing
Authors: Salman Adil K. , Al-Jumaili Mohammed , Sut-Lohmann Magdalena , Durner Wolfgang
Published: December 2024

Measuring soil moisture is essential in various scientific and engineering disciplines. Over recent decades, numerous technologies have been employed for in situ monitoring of soil moisture. Currently, dielectric-based sensors are the most popular measurement technology and provide acceptable accuracy for various measurement purposes. However, these sensors are relatively expensive, and alternative technologies, which are cheaper, are not accurate enough for scientific purposes. Recently, the idea of using a Wi-Fi signal to measure soil moisture has been presented. Theoretically, the use of Wi-Fi technology in soil sensing follows the same concepts as the previous dielectric sensors. The main advantage of Wi-Fi technology is the possibility of providing a relatively accurate and cost-effective solution for soil moisture measurement. In this work, we try to investigate the possibility of using Wi-Fi signal characteristics for soil sensing. Therefore, a series of small-scale laboratory and field experiments were conducted to test the concept. The results of these experiments were promising, showing strong linear relationships between Wi-Fi signal properties (received signal strength indicator, RSSI) and soil water content, with R
2 values ranging between 0.92 and 0.99, indicating a strong correlation. They also illustrate the possibility of using this technology to develop an inexpensive and accurate device for measuring soil moisture. However, observations from the experiments also point to problematic factors involving the hardware and software used in the measurements. It is important to control these factors in the next steps to develop a reliable measurement device.
Exercise and cardiac rehabilitation after LVAD implantation
Authors: Newman Emily , Brailovsky Yevgeniy , Rajapreyar Indranee
Published: December 2024

Left ventricular assist devices (LVAD) have improved mortality and quality of life for patients with end-stage heart failure by providing an alternative to cardiac transplant or as a bridge to transplantation. The improvement in functional capacity however is minimal to modest depending on the right ventricular function, optimal hemodynamics on LVAD therapy, and comorbidities. There is improvement in submaximal exercise capacity but improvement in peak aerobic capacity is limited. Exercise capacity can be improved by referral to cardiac rehabilitation after LVAD implantation. Cardiac rehabilitation is safe and effective with improvement in functional capacity, and decrease in mortality and heart failure hospitalizations. Cardiopulmonary exercise testing (CPET) is a specialized exercise stress test that measures gas exchange during exercise to determine a variety of variables that have been shown to be predictive of mortality in patients undergoing cardiac transplant. CPET is valuable for prognostication and is a predictor of adverse outcomes, including right heart failure in the immediate post-LVAD implantation period, long-term mortality. CPET is an additional testing that can aid in the decision making for LVAD explantation or decommissioning.
Effect of incident light and light gradients on eicosapentaenoic acid distribution between lipid classes in Nannochloropsis oceanica
Authors: Ferrer-Ledo Narcis , van Oossanen Sabine , Wijffels Rene H. , Evers Wendy A. C. , Südfeld Christian , Janssen Marcel , Teles Dominguez Cabanelas Iago , Barbosa Maria J.
Published: December 2024

Commercial production of eicosapentaenoic acid (EPA) from photoautotrophic microalgae like Nannochloropsis oceanica requires higher productivity and larger scales to reduce costs. Improving productivity can be achieved by increasing biomass concentrations, which creates light gradients in the reactor depending on the culture’s acclimation and the reactor geometry. These light gradients affect physiology, lipid synthesis, but also the distribution of fatty acids between lipid classes. In this study we evaluated the combined effect of the incident light intensity and light gradient on growth, biochemical composition, and fatty acid distribution between lipid classes. A total of 13 cultivations were performed in continuous mode using three different incident light intensities (200, 670, and 1550 μmol photons m−2 s−1) and four dilution rates (from 0.29 to 0.75 day−1). Reducing dilution rates resulted in higher biomass concentrations, steeper light gradients, and lower average light intensities. Increasing incident light intensity improved biomass productivity from 0.5 to 1.8 g L−1 day−1, while the biomass yield on light decreased from 1.05 to 0.44 g mol−1. Lowering average light intensities decreased the triglyceride content from 11.1 to 1.5% w/w, and increased the galactolipid content, mainly monogalactosyldiacylglycerol, up from 3.1 to 5.1% w/w. Total EPA contents did not decrease at low incident light but decreased by 28% at highly saturating light, both relative to medium incident light. The EPA content in polar lipids increased at lower average light intensities, and decreased in the neutral fraction simultaneously. These results highlight the tight regulation of EPA content between lipid polar and neutral fractions under different light regimes.

Graphical Abstract
Back-to-basics tutorial: Secondary ion mass spectrometry (SIMS) in ceramics
Authors: Shen Zonghao , Fearn Sarah
Published: December 2024

Secondary ion mass spectrometry (SIMS) is a sophisticated and powerful analytical technique to characterise the surface and sub-surface of materials. It has been widely used in materials science due to its trace level sensitivity to the full range of elements and isotopes, capability of profiling from surface to bulk, and various modes to provide information from the mass spectrum to 2D and 3D elemental distribution. In this article, we will discuss the working principles of SIMS, instrumentation information, issues related to measurements and data analysis with some case studies as well as the possible pitfalls. It will be by no means exhaustive for SIMS analysis but the aim of this article is to lower the boundaries for students and researchers who are going to perform their first SIMS analyses. The examples will be focused on solid state materials for energy applications only, albeit SIMS has been widely used for the surface analysis on all kinds of materials.
Spirituality in Managing Perceived Stress and Promoting Self-Care: A Descriptive Study on Nursing Students in Spain
Authors: Fernández-Pascual M. Dolores , Reig-Ferrer Abilio , Santos-Ruiz Ana M. , Martínez-Rodríguez Laura
Published: December 2024

The relationship between spirituality, perceived stress, and self-care was examined in a sample of 515 nursing students in Spain. Using the perceived stress scale (PSS), the professional self-care scale (PSCS), and the spirituality questionnaire (MiLS-sp/sf), the findings indicated that higher spirituality, particularly through inner peace and faith, was linked to reduced stress and enhanced self-care across physical, inner, and social dimensions. However, the inner self-care dimension was the least developed, suggesting that essential emotional, spiritual, and psychological needs were neglected. This result highlights the necessity for a comprehensive self-care model that empowers students to create personalised strategies to enhance their inner and spiritual self-care. It is essential that these findings give rise to practical applications in order to promote the well-being and professional effectiveness of nursing students.
Adaptive multiplication of $$\mathcal {H}^2$$-matrices with block-relative error control
Authors: Börm Steffen
Published: December 2024

The discretization of non-local operators, e.g., solution operators of partial differential equations or integral operators, leads to large densely populated matrices. $$\mathcal {H}^2$$

H

2

-matrices take advantage of local low-rank structures in these matrices to provide an efficient data-sparse approximation that allows us to handle large matrices efficiently, e.g., to reduce the storage requirements to $$\mathcal {O}(n k)$$

O
(
n
k
)

for n-dimensional matrices with local rank k, and to reduce the complexity of the matrix-vector multiplication to $$\mathcal {O}(n k)$$

O
(
n
k
)

operations. In order to perform more advanced operations, e.g., to construct efficient preconditioners or evaluate matrix functions, we require algorithms that take $$\mathcal {H}^2$$

H

2

-matrices as input and approximate the result again by $$\mathcal {H}^2$$

H

2

-matrices, ideally with controllable accuracy. In this manuscript, we introduce an algorithm that approximates the product of two $$\mathcal {H}^2$$

H

2

-matrices in $$\mathcal {O}(n k^2 \log n)$$

O
(
n

k
2

log
n
)

operations and guarantees block-relative error estimates for the submatrices of the result. It uses specialized tree structures to represent the exact product in an intermediate step, thereby allowing us to apply mathematically rigorous error control strategies.
Future-forming research in higher education: a review of academic advising literature from the United States
Authors: Hutson Bryant L. , He Ye
Published: December 2024

Academic advising is one of the key practices in U.S. higher education institutions for supporting students’ success. However, the complexity of academic advising program structures, the difficulties in identifying appropriate outcome measures, and the lack of inclusion of multiple stakeholders’ perspectives continue to challenge scholars to integrate research in academic advising practices. In this article, we review publications on academic advising that were included in the recent What Works Clearinghouse Practice Guide to highlight methodological challenges and strategies. Based on insights from these studies, we further explore design considerations to balance rigor, replicability, and relevance in academic advising research and propose promising future-forming research design considerations for higher education researchers and practitioners.
Direct Copper Metallization of Carbon Fiber-Reinforced Thermoplastic Polymers for Lightning Strike Protection Using Low-Pressure Cold Spray
Authors: Saito Hiroki , Izumi Atsushi , Meng Yuxian , Ichikawa Yuji , Ogawa Kazuhiro , Ishida Syoma , Naruse Yoshihiro , Nishizaki Akihiko
Published: December 2024

Metallizing polymer composite via cold spray is an attractive process for producing lightning strike protection (LSP) in composite-based aircraft. However, direct deposition of copper, the most common conductive metal, on carbon fiber-reinforced thermoplastic polymers (CFRTP) remains challenging due to the severe polymer erosion and carbon fiber fracture induced by cold-sprayed multi-particle impact. In this work, the copper direct deposition window was explored by varying copper particle size and operating gas temperature, which are primary parameters determining particle impact energy. Following this, a lightning strike test was performed to evaluate the protective effectiveness of the deposited copper coating in reducing damage to the underlying CFRTP substrate. It was revealed that fine copper particles approximately 5 µm in diameter are effective for direct deposition due to their minimal induction of polymer erosion. Sufficient heating of the particle spray area above the glass transition temperature promoted continuous coating formation. The lightning strike tests demonstrated that the cold-sprayed copper coating effectively protects the underlying CFRTP by acting as a major electric current path and a sacrificial protective layer. These findings highlight the promising potential of cold spray as a new LSP technology for polymer composite aircraft.
Construction of a prediction model for Alzheimer’s disease using an AI-driven eye-tracking task on mobile devices
Authors: Li Qinjie , Yan Jiaxin , Ye Jianfeng , Lv Hao , Zhang Xiaochen , Tu Zhilan , Li Yunxia , Guo Qihao
Published: December 2024

Background

Eye-movement can reflect cognition and provide information on the neurodegeneration, such as Alzheimer’s disease (AD). The high cost and limited accessibility of eye-movement recordings have hindered their use in clinics.

Aims

We aim to develop an AI-driven eye-tracking tool for assessing AD using mobile devices with embedded cameras.

Methods

166 AD patients and 107 normal controls (NC) were enrolled. The subjects completed eye-movement tasks on a pad. We compared the demographics and clinical features of two groups. The eye-movement features were selected using least absolute shrinkage and selection operator (LASSO). Logistic regression (LR) model was trained to classify AD and NC, and its performance was evaluated. A nomogram was established to predict AD.

Results

In training set, the model showed a good area under curve (AUC) of 0.85 for identifying AD from NC, with a sensitivity of 71%, specificity of 84%, positive predictive value of 0.87, and negative predictive value of 0.65. The validation of the model also yielded a favorable discriminatory ability with the AUC of 0.91, sensitivity, specificity, positive predictive value, and negative predictive value of 82%, 91%, 0.93, and 0.77 to identify AD patients from NC.

Discussion and Conclusions

This novel AI-driven eye-tracking technology has the potential to reliably identify differences in eye-movement abnormalities in AD. The model shows excellent diagnostic performance in identifying AD based on the current data collected. The use of mobile devices makes it accessible for AD patients to complete tasks in primary clinical settings or follow up at home.
Investigating the effect of sediment loading on the growth of a shale-cored anticline using finite element modelling: an example from the South Caspian Basin
Authors: Procter Andrew , Roberts Daniel T. , Lonergan Lidia , Dee Stephen J.
Published: December 2024

Large-scale folding of sedimentary rock is generally considered to be a response to horizontal tectonic shortening. We test an alternative hypothesis where we propose that in basins with high sedimentation rates where folds are cored by mechanically weak mobile shale, fold growth can be amplified by the gravitational loading of the weak underlying shale. We use two-dimensional plane-strain, finite element code to investigate the mechanics of growth of a shale-cored fold in the South Caspian Sea Basin, where c.10 km of sediment was deposited in the last 6 My. The overburden and syn-kinematic sediments are modelled as poro-elastoplastic materials using a modified Cam-Clay critical state model and the mobile shale is modelled as visco-plastic Herschell-Bulkley material, representative of conditions at critical state. The results show that the atypical geometries of the fold strata can be explained by the application of horizontal shortening and simultaneous sediment loading of the visco-plastic layer. The viscosity of the shale determines whether differential loading will cause fold growth and its density controls the magnitude of fold amplification, with a lower density causing greater fold amplification. Results demonstrate that the magnitude of shale inflation is controlled by complex interaction of the relative amounts of shortening and sedimentation rate.
A new grey model with generalized fractal-fractional derivative for prediction of tourism development
Authors: Xu Chenhui , Zheng Jianguo
Published: December 2024

A new fractional order grey prediction model is proposed for accurate forecasting of tourism development in China. The model combines generalized fractal-fractional derivative operators with difference and accumulation generation operators. Experimental comparisons with existing models show significant improvements in accuracy and efficiency. The model is applied to forecast tourism development in China and results are compared with actual data to verify effectiveness. The proposed model combines fractal-fractional operators to improve prediction accuracy and efficiency, accounting for various factors affecting tourism development. Comparisons with existing models show superiority in accuracy and efficiency. The model accurately predicts tourism development in China, resulting in improved forecasting compared to existing methods. Comparison with actual data further validates the model by displaying agreement between predicted and actual values. Overall, the proposed model effectively captures tourism development dynamics in China for accurate forecasting.