bluuebunny/crossref_metadata_2025_split huggingface dataset:
PI3K/AKT signaling activation by roflumilast ameliorates rotenone-induced Parkinson’s disease in rats
Authors: Farid Heba A. , Sayed Rabab H. , El-Shamarka Marwa El-Sayed , Abdel-Salam Omar M. E. , El Sayed Nesrine S. 
Published: August 2023

AbstractParkinson’s disease (PD) is the second most common progressive age-related neurodegenerative disorder. Paramount evidence shed light on the role of PI3K/AKT signaling activation in the treatment of neurodegenerative disorders. PI3K/AKT signaling can be activated via cAMP-dependent pathways achieved by phosphodiesterase 4 (PDE4) inhibition. Roflumilast is a well-known PDE4 inhibitor that is currently used in the treatment of chronic obstructive pulmonary disease. Furthermore, roflumilast has been proposed as a favorable candidate for the treatment of neurological disorders. The current study aimed to unravel the neuroprotective role of roflumilast in the rotenone model of PD in rats. Ninety male rats were allocated into six groups as follows: control, rotenone (1.5 mg/kg/48 h, s.c.), L-dopa (22.5 mg/kg, p.o), and roflumilast (0.2, 0.4 or 0.8 mg/kg, p.o). All treatments were administrated for 21 days 1 h after rotenone injection. Rats treated with roflumilast showed an improvement in motor activity and coordination as well as preservation of dopaminergic neurons in the striatum. Moreover, roflumilast increased cAMP level and activated the PI3K/AKT axis via stimulation of CREB/BDNF/TrkB and SIRT1/PTP1B/IGF1 signaling cascades. Roflumilast also caused an upsurge in mTOR and Nrf2, halted GSK-3β and NF-ĸB, and suppressed FoxO1 and caspase-3. Our study revealed that roflumilast exerted neuroprotective effects in rotenone-induced neurotoxicity in rats. These neuroprotective effects were mediated via the crosstalk between CREB/BDNF/TrkB and SIRT1/PTP1B/IGF1 signaling pathways which activates PI3K/AKT trajectory. Therefore, PDE4 inhibition is likely to offer a reliable persuasive avenue in curing PD via PI3K/AKT signaling activation.
Graphical Abstract
Detection of Iterative Adversarial Attacks via Counter Attack
Authors: Rottmann Matthias , Maag Kira , Peyron Mathis , Gottschalk Hanno , Krejić Nataša 
Published: August 2023

AbstractDeep neural networks (DNNs) have proven to be powerful tools for processing unstructured data. However, for high-dimensional data, like images, they are inherently vulnerable to adversarial attacks. Small almost invisible perturbations added to the input can be used to fool DNNs. Various attacks, hardening methods and detection methods have been introduced in recent years. Notoriously, Carlini–Wagner (CW)-type attacks computed by iterative minimization belong to those that are most difficult to detect. In this work we outline a mathematical proof that the CW attack can be used as a detector itself. That is, under certain assumptions and in the limit of attack iterations this detector provides asymptotically optimal separation of original and attacked images. In numerical experiments, we experimentally validate this statement and furthermore obtain AUROC values up to $$99.73\%$$

99.73
%

on CIFAR10 and ImageNet. This is in the upper part of the spectrum of current state-of-the-art detection rates for CW attacks.
Validation of the bowel urgency numeric rating scale in patients with Crohn’s disease: results from a mixed methods study
Authors: Dubinsky Marla C. , Delbecque Laure , Hunter Theresa , Harding Gale , Stassek Larissa , Moses Richard E. , Lewis James D. 
Published: August 2023

Abstract
Purpose
Bowel urgency (BU) is an important symptom of Crohn’s disease (CD), however there is no patient-reported outcome (PRO) scale validated in this population to assess BU severity. Here we evaluated the content validity and psychometric properties of the Urgency Numeric Rating Scale (NRS).

Method
Qualitative interviews were conducted with moderate-to-severe CD participants to confirm importance and relevance of BU in this population, cognitively debrief the Urgency NRS, and explore score interpretation and CD remission. A quantitative web survey study was conducted to explore the measurement properties of the urgency NRS.

Results
Qualitative Interview: 34 of 35 participants reported BU. It was most bothersome for 44%, 47% reported it daily, 18% with every bowel movement. BU had a severe impact on daily activities, causing many participants to stay home more than preferred. Patients confirmed the relevance, appropriateness, comprehensibility of the item, recall period, response options, and instructions of the Urgency NRS. Small reductions on the Urgency NRS score reflected meaningful improvements. Quantitative survey: The study sample comprised 76 participants (65.8% female). Mean Urgency NRS score was 4.7 (SD 2.26; N = 76) at Week 1, with no floor/ceiling effect. Test–retest reliability was acceptable. Construct and known-groups validity against selected PROs were overall strong and within ranges hypothesized a priori.

Conclusion
The Urgency NRS is a valid and reliable instrument to assess BU severity in CD.
Fairness of artificial intelligence in healthcare: review and recommendations
Authors: Ueda Daiju , Kakinuma Taichi , Fujita Shohei , Kamagata Koji , Fushimi Yasutaka , Ito Rintaro , Matsui Yusuke , Nozaki Taiki , Nakaura Takeshi , Fujima Noriyuki , Tatsugami Fuminari , Yanagawa Masahiro , Hirata Kenji , Yamada Akira , Tsuboyama Takahiro , Kawamura Mariko , Fujioka Tomoyuki , Naganawa Shinji 
Published: August 2023

AbstractIn this review, we address the issue of fairness in the clinical integration of artificial intelligence (AI) in the medical field. As the clinical adoption of deep learning algorithms, a subfield of AI, progresses, concerns have arisen regarding the impact of AI biases and discrimination on patient health. This review aims to provide a comprehensive overview of concerns associated with AI fairness; discuss strategies to mitigate AI biases; and emphasize the need for cooperation among physicians, AI researchers, AI developers, policymakers, and patients to ensure equitable AI integration. First, we define and introduce the concept of fairness in AI applications in healthcare and radiology, emphasizing the benefits and challenges of incorporating AI into clinical practice. Next, we delve into concerns regarding fairness in healthcare, addressing the various causes of biases in AI and potential concerns such as misdiagnosis, unequal access to treatment, and ethical considerations. We then outline strategies for addressing fairness, such as the importance of diverse and representative data and algorithm audits. Additionally, we discuss ethical and legal considerations such as data privacy, responsibility, accountability, transparency, and explainability in AI. Finally, we present the Fairness of Artificial Intelligence Recommendations in healthcare (FAIR) statement to offer best practices. Through these efforts, we aim to provide a foundation for discussing the responsible and equitable implementation and deployment of AI in healthcare.
Right Information, Right Patient, Right Time: Utilizing the MyCareCompass Platform to Deliver Patient Education in the Oncology Setting
Authors: Fleisher Linda , Kenny Cassidy , Rusten Cheryl , Koren Daniella , Landau Zoe 
Published: August 2023

AbstractPatient education is an important part of cancer care as it increases patient activation and informed decision-making, reduces anxiety, and improves outcomes. However, challenges to providing appropriate education to patients exist on both the health provider and patient side of the equation, e.g., time constraints and health literacy issues. Digital health education is a fast-growing field of interest that has been shown to improve health outcomes, increase effectiveness of medical treatments and education, lower medical costs, and enhance both clinical diagnosis and research opportunities by streamlining data collection, sharing, and analysis. In 2019, Fox Chase Cancer Center was selected by ARCHES, an established patient education software company, to pilot its award-winning digital patient engagement system MyCareCompass. During the pilot, patients scheduled for port insertions were sent electronic messages inviting them to review various online educational materials related to their procedure and subsequent concerns. The invitations and resources were seamlessly integrated into the scheduling system and timed to arrive when patients would most need them. There was high usage of the port-related materials and patients reported a high level of satisfaction with the delivery system and the information. This automated process of delivering high-quality and relevant patient education was able to be implemented smoothly with IT involvement, had a positive impact on patients without adding any extra burden to the care team, and highlighted opportunities to integrate these types of interventions into routine care.
Compliance with and enforcement mechanism of labor law: cost-benefits analysis from employers’ perspective in Bangladesh
Authors: Syed Robayet Ferdous 
Published: August 2023

AbstractThis manuscript offers a qualitative exploration aimed at proposing effective strategies for enhancing compliance with and enforcement of labor laws in Bangladesh by diminishing the incentives for non-compliance. The study relies on primary data obtained from statutes, legal decisions, and secondary data sourced from scholarly articles, books, and book chapters, among others. Employing a cost-benefit analysis approach from the employers’ perspective, the study contends that showcasing the superior costs associated with violating labor laws, in comparison to the benefits gained, will incentivize employers to prioritize compliance to safeguard their interests. To this end, the research puts forth eight distinct techniques or mechanisms to curtail the benefits derived from disregarding labor laws. These strategies are thoughtfully organized into two categories, namely “increasing the likelihood of self-enforcement” and “supporting by other actors.” The proposed techniques for enhancing compliance with and enforcement of labor laws in Bangladesh hold significant potential in benefiting key stakeholders, policymakers, and practitioners in the field. Furthermore, the study’s findings carry valuable implications for other developing countries in the South Asian region, given their similar socio-economic and cultural contexts.
Numerical analysis of high-speed railway slab tracks using calibrated and validated 3D time-domain modelling
Authors: Esen A. F. , Laghrouche O. , Woodward P. K. , Medina-Pineda D. , Corbisez Q. , Shih J. Y. , Connolly D. P. 
Published: August 2023

AbstractConcrete slabs are widely used in modern railways to increase the inherent resilient quality of the tracks, provide safe and smooth rides, and reduce the maintenance frequency. In this paper, the elastic performance of a novel slab trackform for high-speed railways is investigated using three-dimensional finite element modelling in Abaqus. It is then compared to the performance of a ballasted track. First, slab and ballasted track models are developed to replicate the full-scale testing of track sections. Once the models are calibrated with the experimental results, the novel slab model is developed and compared against the calibrated slab track results. The slab and ballasted track models are then extended to create linear dynamic models, considering the track geodynamics, and simulating train passages at various speeds, for which the Ledsgård documented case was used to validate the models. Trains travelling at low and high speeds are analysed to investigate the track deflections and the wave propagation in the soil, considering the issues associated with critical speeds. Various train loading methods are discussed, and the most practical approach is retained and described. Moreover, correlations are made between the geotechnical parameters of modern high-speed rail and conventional standards. It is found that considering the same ground condition, the slab track deflections are considerably smaller than those of the ballasted track at high speeds, while they show similar behaviour at low speeds.
Density kernel depth for outlier detection in functional data
Authors: Hernández Nicolás , Muñoz Alberto , Martos Gabriel 
Published: August 2023

AbstractIn this paper, we propose a novel approach to address the problem of functional outlier detection. Our method leverages a low-dimensional and stable representation of functions using Reproducing Kernel Hilbert Spaces (RKHS). We define a depth measure based on density kernels that satisfy desirable properties. We also address the challenges associated with estimating the density kernel depth. Throughout a Monte Carlo simulation we assess the performance of our functional depth measure in the outlier detection task under different scenarios. To illustrate the effectiveness of our method, we showcase the proposed method in action studying outliers in mortality rate curves.
Vicarious Emotions of Fear and Pain in Rodents
Authors: Keysers Christian , Gazzola Valeria 
Published: August 2023

AbstractAffective empathy, the ability to share the emotions of others, is an important contributor to the richness of our emotional experiences. Here, we review evidence that rodents show signs of fear and pain when they witness the fear and pain of others. This emotional contagion creates a vicarious emotion in the witness that mirrors some level of detail of the emotion of the demonstrator, including its valence and the vicinity of threats, and depends on brain regions such as the cingulate, amygdala, and insula that are also at the core of human empathy. Although it remains impossible to directly know how witnessing the distress of others feels for rodents, and whether this feeling is similar to the empathy humans experience, the similarity in neural structures suggests some analogies in emotional experience across rodents and humans. These neural homologies also reveal that feeling distress while others are distressed must serve an evolutionary purpose strong enough to warrant its stability across ~ 100 millions of years. We propose that it does so by allowing observers to set in motion the very emotions that have evolved to prepare them to deal with threats — with the benefit of triggering them socially, by harnessing conspecifics as sentinels, before the witness personally faces that threat. Finally, we discuss evidence that rodents can engage in prosocial behaviors that may be motivated by vicarious distress or reward.
The effect of air plasma cutting on the quality, structural transformations and changes in the chemical composition of structural steel
Authors: Górka Jacek 
Published: August 2023

Abstract
The article presents results of tests concerning the effect of technological parameters of the plasma arc cutting process (involving the use of air as plasma gas) on the quality of cut surfaces as well as on structural transformations and changes in the chemical composition of 14 mm-thick plates made of steel S235JR. The tests revealed that the adjustment of optimum parameters of the cutting process enabled the obtainment of cut surfaces representing quality class I in accordance with the ISO 9013 standard. Only the surfaces processed using the maximum cutting rates represented quality class II. The chemical composition analysis was performed using an ICXA 733 X-ray microanalyser (Jeol) equipped with an energy-dispersive spectrometer (EDS) and an ISIS 300 analytical system (OXFORD). The cut surfaces were observed and their characteristic areas were photographed using an X-ray microanalyser and the backscattered electrons (BSE) technique. The phase analysis was performed using a PHILIPS PW 1050 X’Change machine operated in the B–B (Bragg–Brentano) geometry. It was observed that the application of the air plasma cutting process led to the formation of an amorphous phase on the cut surface. The amorphous phase was characterised by a very high nitrogen content (of approximately 1.6%) and a hardness of 750 HV 0.2. The intense nitration resulted from the diffusion of nitrogen from the plasma gas. At the same time, the effect of air plasma arc gases on the liquid metal was responsible for the carburising of the cut surface (up to approximately 0.5%) and the burnout of alloying components (in accordance with the theory of the selective oxidation of chemical elements). The quality of the cut surfaces was primarily affected by the cutting rate. An increase in the cutting rate was accompanied by the deterioration of the geometric features of cut surfaces. In addition, higher cutting rates also translated into the significant reduction of the HAZ width and that of the size of the zone of chemical composition changes. The tests revealed that, in terms of the 14 mm-thick plates made of steel S235JR, the optimum cutting rates were restricted within the range of 600 mm/min to 1500 mm/min. The tests carried out made it possible to determine the influence of the active plasma gas (oxygen, nitrogen) both on changes in the chemical composition of the tested steel and on the quality of the cut surfaces obtained.
Gauss–Newton method for solving linear inverse problems with neural network coders
Authors: Scherzer Otmar , Hofmann Bernd , Nashed Zuhair 
Published: August 2023

AbstractNeural networks functions are supposed to be able to encode the desired solution of an inverse problem very efficiently. In this paper, we consider the problem of solving linear inverse problems with neural network coders. First we establish some correspondences of this formulation with existing concepts in regularization theory, in particular with state space regularization, operator decomposition and iterative regularization methods. A Gauss–Newton method is suitable for solving encoded linear inverse problems, which is supported by a local convergence result. The convergence studies, however, are not complete, and are based on a conjecture on linear independence of activation functions and its derivatives. Some numerical experiments are presented to support the theoretical findings.
Urban cooling potential and cost comparison of heat mitigation techniques for their impact on the lower atmosphere
Authors: Khan Ansar , Carlosena Laura , Khorat Samiran , Khatun Rupali , Das Debashish , Doan Quang-Van , Hamdi Rafiq , Aziz Sk Mohammad , Akbari Hashem , Santamouris Mattheos , Niyogi Dev 
Published: August 2023

AbstractCool materials and rooftop vegetation help achieve urban heating mitigation as they can reduce building cooling demands. This study assesses the cooling potential of different mitigation technologies using Weather Research and Forecasting (WRF)- taking case of a tropical coastal climate in the Kolkata Metropolitan Area. The model was validated using data from six meteorological sites. The cooling potential of eight mitigation scenarios was evaluated for: three cool roofs, four green roofs, and their combination (cool-city). The sensible heat, latent heat, heat storage, 2-m ambient temperature, surface temperature, air temperature, roof temperature, and urban canopy temperature was calculated. The effects on the urban boundary layer were also investigated.The different scenarios reduced the daytime temperature of various urban components, and the effect varied nearly linearly with increasing albedo and green roof fractions. For example, the maximum ambient temperature decreased by 3.6 °C, 0.9 °C, and 1.4 °C for a cool roof with 85% albedo, 100% rooftop vegetation, and their combination.The cost of different mitigation scenarios was assumed to depend on the construction options, location, and market prices. The potential for price per square meter and corresponding temperature decreased was related to one another. Recognizing the complex relationship between scenarios and construction options, the reduction in the maximum and minimum temperature across different cool and green roof cases were used for developing the cost estimates. This estimate thus attempted a summary of the price per degree of cooling for the different potential technologies.Higher green fraction, cool materials, and their combination generally reduced winds and enhanced buoyancy. The surface changes alter the lower atmospheric dynamics such as low-level vertical mixing and a shallower boundary layer and weakened horizontal convective rolls during afternoon hours. Although cool materials offer the highest temperature reductions, the cooling resulting from its combination and a green roof strategy could mitigate or reverse the summertime heat island effect. The results highlight the possibilities for heat mitigation and offer insight into the different strategies and costs for mitigating the urban heating and cooling demands.
Love matters: the case for an inclusive, contemporary approach to romance themes and texts in subject English
Authors: Nichols Sue 
Published: August 2023

AbstractThis paper examines analyses of adolescent romance fiction, highlighting key themes and debates over time. I will argue that contemporary social conditions underline the need to reconsider the value of this genre in the secondary English classroom. However, working effectively with genre literature (including romance) requires educators to diversify reading practices, challenging the dominance of the standard ‘class novel’ approach. I will describe the integration of a module on teen romance into a literature course for preservice English educators. Finally, focusing on a specific text,Frankly in Loveby David Yoon, I highlight the skilful way in which authors of contemporary adolescent literature weave multiple perspectives into engaging and nuanced narratives in which characters navigate identities, relationships, and ideas about love.
Evaluating Spatial, Cause-Specific and Seasonal Effects of Excess Mortality Associated with the COVID-19 Pandemic: The Case of Germany, 2020
Authors: Mühlichen Michael , Sauerberg Markus , Grigoriev Pavel 
Published: August 2023

AbstractBackgroundEvaluating mortality effects of the COVID-19 pandemic using all-cause mortality data for national populations is inevitably associated with the risk of masking important subnational differentials and hampering targeted health policies. This study aims at assessing simultaneously cause-specific, spatial and seasonal mortality effects attributable to the pandemic in Germany in 2020.MethodsOur analyses rely on official cause-of-death statistics consisting of 5.65 million individual death records reported for the German population during 2015–2020. We conduct differential mortality analyses by age, sex, cause, month and district (N = 400), using decomposition and standardisation methods, comparing each strata of the mortality level observed in 2020 with its expected value, as well as spatial regression to explore the association of excess mortality with pre-pandemic indicators.ResultsThe spatial analyses of excess mortality reveal a very heterogenous pattern, even within federal states. The coastal areas in the north were least affected, while the south of eastern Germany experienced the highest levels. Excess mortality in the most affected districts, with standardised mortality ratios reaching up to 20%, is driven widely by older ages and deaths reported in December, particularly from COVID-19 but also from cardiovascular and mental/nervous diseases.ConclusionsOur results suggest that increased psychosocial stress influenced the outcome of excess mortality in the most affected areas during the second lockdown, thus hinting at possible adverse effects of strict policy measures. It is essential to accelerate the collection of detailed mortality data to provide policymakers earlier with relevant information in times of crisis.