bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effects of low HER2 expression on survival in patients with metastatic breast cancer treated with CDK 4/6 inhibitors: a multicenter retrospective study
Authors: Guliyev Murad , Şen Gülin Alkan , Gültürk İlkay , Majidova Nargiz , Akdağ Goncagül , Ahadzade Ali , Turna Hande , Demirci Nebi Serkan 
Published: March 2024

Abstract
Purpose
Endocrine therapy (ET) in combination with CDK 4/6 inhibitors (CDK 4/6i) is the standard treatment modality for hormone receptor (HR)-positive and HER2-negative metastatic breast cancer (mBC). There is uncertainty about the prognostic and predictive value of HER2-low status and whether HER2-low BC is an individual biologic subtype. In this study, we aimed to investigate the prognostic effect of HER2 expression status on survival in mBC patients treated with first-line ET plus CDK 4/6i.

Methods
This multicenter retrospective study included patients with HR + /HER2-negative mBC cancer who were treated with first-line CDK 4/6i in combination with ET from January 2016 to March 2023. Patients were divided into two groups (HER2-low and zero), and survival and safety analyses were performed.

Results
A total of 201 patients were included in this study; of these, 73 (36.3%) had HER2-low disease and 128 (63.7%) had HER2-zero. There were 135 patients (67.2%) treated with ribociclib and 66 (32.8%) with palbociclib. Most of the patients (75.1%) received aromatase inhibitors as combination-endocrine therapy. Baseline characteristics were similar between the two groups. The median follow-up was 19.1 months (range: 2.5–78.4). The most common side effect was neutropenia (22.4%). The frequency of grade 3–4 toxicity was similar between the HER2-zero and low patients (32% vs 31.5%; p = 0.939). Visceral metastases were present in 44.8% of patients. Between the HER2-low and zero groups, median PFS (25.2 vs 22.6 months, p = 0.972) and OS (not reached vs 37.5 months, p = 0.707) showed no statistically significant differences.

Conclusion
The prognostic value of HER2-low status remains controversial. Our study showed no significant effect of HER2 low expression on survival in patients receiving CDK 4/6i plus ET.
Acetylation of cotton knitted fabrics for improved quick drying after water absorption
Authors: Onodera Satoru , Tanaka Chiaki , Isogai Akira 
Published: March 2024

AbstractQuick drying after water or sweat absorption is an important function of underwear. In this study, the hydroxy groups of cotton knitted fabrics (CFs) were partially acetylated, maintaining the original fabric structure. The following three heterogeneous acetylation processes were used: Ac-I (Ac2O/H2SO4/toluene), Ac-II (Ac2O/H2SO4/AcOH/water), and Ac-III (Ac2O/AcONa) systems (Ac2O, acetic anhydride; AcOH, acetic acid; AcONa, sodium acetate). Acetylated cotton knitted fabrics (AcCFs) with degree of substitution (DS) ≤ 0.5 and yields of > 80% were prepared. AcCFs prepared with the Ac-III system gave high degree of polymerization (DP) values of > 1500, whereas those prepared with the Ac-II system exhibited low DP values of ≤ 400. The moisture contents of AcCFs at 20 °C and 65% relative humidity decreased from 7.1 to 4.7% with increasing DS value up to 0.46; introducing hydrophobic acetyl groups into the CFs decreased their hydrophilic nature. Quick drying similar to that of a polyester fabric was achieved for some of the AcCFs with DS values of < 0.2. When the acetyl groups in the AcCFs were homogeneously distributed across each fiber width (achieved for AcCFs prepared with the Ac-II system), quick drying was evident in the AcCFs. The crystallinities and crystal widths of cellulose I for the AcCFs with DS values of ≤ 0.28 were almost unchanged compared with those of the original CFs. However, neither the crystallinities nor crystal widths of cellulose I were directly related to quick drying after water absorption. Thermal degradation of the AcCFs varied between the acetylation systems, and depended on the DP values and/or the presence of sulfate ester groups in the AcCFs.
Graphical Abstract
Attention and Interpretation Bias Modification Transfers to Memory Bias: Testing the Combined Cognitive Bias Hypothesis
Authors: Zhang Zhen , Vrijsen Janna N. , Sanchez-Lopez Alvaro , Koster Ernst H.W. , Becker Eni S. 
Published: March 2024

Abstract
Purpose
This study delves into the combined cognitive bias hypothesis in depression, exploring the interaction between negative attention, interpretation and memory biases. We aimed to assess whether modifying attention and interpretation bias would lead to congruent changes in memory bias, and to what extend and depth this causal effect can be.

Method
Ninety-nine undergraduates underwent either a positive (PT) or negative (NT) four-day attention and interpretation bias training. A set of well-established post-training assessments including free recall, recognition, autobiographic memory, and self-reference encoding tasks were used to evaluate memory bias. Affective states were measured pre- and post-training.

Results
Compared to PT, participants in NT correctly retrieved more negative trained stimuli, and falsely recognized more negative synonyms of trained terms. NT also exhibited an enhanced retrieval of negative autobiographical memory. No significant differences were found between NT and PT in self-referential encoding and retrieval bias, or affective states.

Discussion
The results suggested an extensive and strong transfer effect from attention and interpretation bias modification to different facets of memory bias, being found in retrieving trained emotional stimuli, in memory intrusion of negative synonyms, and in autobiographic memory recall. The findings underscored the causality between three biases, supporting the combined cognitive bias hypothesis. It might also suggest an effective new approach to modify memory bias via attention and interpretation bias training.
Game-based learning in metaverse: Virtual chemistry classroom for chemical bonding for remote education
Authors: Rahman Hameedur , Wahid Samiya Abdul , Ahmad Faizan , Ali Numan 
Published: March 2024

AbstractVirtual classrooms based on the metaverse or virtual reality are useful and effective for imparting basic chemistry concepts. Interactive and immersive environments can effectively teach fundamental chemistry concepts, such as chemical bonding and formulas, thereby making these otherwise abstract and intangible ideas more accessible and understandable. With the outbreak of Covid-19, e-learning platforms have also been developed for chemistry education. However, these platforms are unable to make learning chemistry interactive and enjoyable. Therefore, there is a need to motivate students to learn basic chemistry concepts in an immersive and interactive environment. In this paper, we propose an immersive virtual reality-based Virtual Chemistry Classroom for Chemical Bonding (VC3B) to facilitate the learning of chemical bonding and formulas through a game-based learning approach. It includes two different games for learning chemical bonding and formulas. In the first game, molecule construction, students reconstruct the structure of molecules by rearranging the atoms in order to learn about chemical bonding. In the second game, chemical formula, students compose the chemical formula of a given compound to help them memorize chemical formulas. The study, conducted on 90 middle school students, employed a randomized controlled study design, dividing participants into three groups. Each group learned about chemical bonding and formulas through three different mediums. After conducting the experiment, the students were given a questionnaire to evaluate the usability of VC3B. The results of the study were positive, with participants finding the VC3B to be more interactive than traditional book and online lecture methods. Participants were also motivated to learn and enhance their knowledge of chemistry.
Area-Based Hedonic Pricing of Urban Green Amenities in Beijing: A Spatial Piecewise Approach
Authors: Liu Zhaoyang , Huang Heqing , Siikamäki Juha , Xu Jintao 
Published: March 2024

AbstractThis study explores a spatial piecewise approach for the hedonic valuation of the area of urban green space at different distances from a property, using a rich census dataset collected from Beijing. We explore three novel empirical strategies that improve the identification of the spatial boundary or threshold distance within which green space is capitalised into housing prices. We first delineated a series of concentric circles surrounding each property and measured the area of green space within each doughnut-shaped ring. We next estimated the hedonic price using three methods. The first is a regression spline model combined with a machine learning type of model selection procedure which objectively selects the exact location of the threshold distance that optimises the model’s predictive performance. The second is a novel matching algorithm that minimises covariate imbalance for a continuous treatment variable (i.e., the area of green space) to provide stronger causal evidence on the hedonic prices of green space at different distances. The third is a spatial difference-in-differences approach that further accounts for endogeneity bias associated with unobserved factors. For our dataset, we found that housing prices are more likely to be affected by green space within a 1 km radius.
Social life cycle assessment of the olive oil industry: a case study in Guilan Province, Iran
Authors: Safeie-Noghlbari Behzad , Amiri Zahra , Allahyari Mohammad Sadegh , Nikkhah Amin , Ben Hassen Tarek , Bacenetti Jacopo 
Published: March 2024

AbstractOlive oil production has severe environmental consequences, including resource depletion, land degradation, carbon emissions, and waste generation. As a result, for over two decades, environmental life cycle assessment (ELCA) has been applied to the olive oil industry to identify environmental issues and reduce the environmental effects. However, little is known regarding the social sustainability of this industry. Social life cycle assessment (S-LCA) has been established as one of the most effective methodologies for assessing the social implications of products throughout their life cycles. Accordingly, based on the S-LCA approach, this study aims to assess the social impacts of the olive oil extraction industry in Roudbar County in Guilan Province in Iran, the major producer of olives and olive oil. The S-LCA model adopted in this paper is built in four major phases (UNEP/SETAC in Guidelines for social life cycle assessment of products, 2009): (1) Definition of Goal and Scope: outlines the intended use and the goal pursued and specifies the scope of the research. The research will then be defined to fulfill that purpose within any constraints. (2) Life Cycle Inventory analysis: is the phase at which data are collected, systems are modeled, and LCI results are generated. (3) Life Cycle Impact Assessment: a collection of steps to obtain data categorization, aggregation, and characterization based on performance reference points. (4) Life Cycle Interpretation: considers all important aspects of the research when drawing results, offering recommendations, and reporting. The findings suggested that the social conditions governing the olive oil extraction cycle in the study area are almost adequate. However, other categories of social impacts, such as cultural heritage, community development, and working conditions, were rated unsatisfactory by olive orchard workers and need improvement. Adopting the cause-and-effect chain in this study favors identifying specific indicators based on social issues in the study location. On the other hand, a scale-based assessment may result in the subjectivity of the results, which adds to the uncertainty. An impact-based assessment may be applied to analyze social impacts such as occupational health and safety, employment, pay, and benefits to get more credible social impact data. Consequently, integrating the scale-based approach with an efficient path-based method may improve its effectiveness.
Ambivalence in Environmental Care: Marine Care Ethics and More-Than-Human Relations in the Conservation of Seagrass Posidonia oceanica
Authors: Cañada Jose A. 
Published: March 2024

AbstractPosidonia oceanicais an endemic seagrass from the mediterranean that provides key ecosystem services. A protected species, its presence is regressing due to anthropogenic pressures, some associated to the tourism economy that much of the Mediterranean coast depends on. In 1992, the European Union declared it a priority habitat, and since the early 2000s, it has occupied a central space in marine conservation debates in the Balearic Islands. Popularly known as Posidonia, this seagrass went from being considereddirtthat ruinedvirginBalearic beaches to become an emblematic species. This article takes this U-turn in policy and public perception as a study case to think of knowledge-making practices and restoration initiatives as a form of environmental care. The relational, situated and affective character of care ethics helps to understand the human and ecological labour embedded in knowledge-making and restoration practices and its inevitable engagement with the Balearic tourism industry. Drawing on those engagements, I reflect on environmental care practices of knowledge-making and restoration, arguing that they emerge ambivalently: they challenge management logics based on economic rationales while forced to develop and coexist inside those same rationales. I conclude by arguing that developing care-centric narratives for environmental conservation and restoration is essential to continue promoting more-than-human aquatic relations in which the needs of others are the ethical basis for action.
Bone formation by Irisin-Poly vinyl alchol modified bioglass ceramic beads in the rabbit model
Authors: Park Seong-Su , Farwa Ume , Kim Hai-Doo , Kim Yong-Sik , Lee Byong-Taek 
Published: March 2024

AbstractIn the aging society, slow bone regeneration poses a serious hindrance to the quality of life. To deal with this problem, in this study, we have combined irisin with the bioglass regular beads to enhance the bone regeneration process. For this purpose, highly porous bioglass was obtained as spherical beads by using sodium alginate. The bioglass was evaluated by various analytical techniques such as SEM, EDS, XRD, and pore size distribution. The results depicted that porous bioglass was prepared correctly and SEM analysis showed a highly porous bioglass was formulated. On this bioglass, irisin was loaded with the assistance of polyvinyl alcohol (PVA) in three concentrations (50 ng/ml, 100 ng/ml, and 150 ng/ml per 1 g of bioglass). SEM analysis showed that pores are covered with PVA. The irisin release profile showed a sustained release over the time period of 7 days. In vitro, biocompatibility evaluation by the MC3T3E1 cells showed that prepared bioglass and irisin loaded bioglass (BGI50, BGI100, and BG150) are highly biocompatible. Alizarin Red staining analysis showed that after 2 weeks BGI50 samples showed highest calcium nodule formation. In vivo in the rabbit femur model was conducted for 1 and 2 months. BGI150 samples showed highest BV/TV ratio of 37.1 after 2 months. The histological data showed new bone formation surrounding the beads and with beads loaded with irisin. Immunohistochemistry using markers OPN, RUNX, COL, and ALP supported the osteogenic properties of the irisin-loaded bioglass beads. The results indicated that irisin-loaded bioglass displayed remarkable bone regeneration.
Graphical Abstract
$$C^{\infty }$$-Regularization by Noise of Singular ODE’s
Authors: Amine Oussama , Baños David , Proske Frank 
Published: March 2024

AbstractIn this paper we construct a new type of noise of fractional nature that has a strong regularizing effect on differential equations. We consider an equation driven by a highly irregular vector field and study the effect of this noise on such dynamical systems. We employ a new method to prove existence and uniqueness of global strong solutions, where classical methods fail because of the “roughness” and non-Markovianity of the driving process. In addition, we prove the rather remarkable property that such solutions are infinitely many times classically differentiable with respect to the initial condition in spite of the vector field being discontinuous. The technique used in this article corresponds, in a certain sense, to the Nash–Moser iterative scheme in combination with a new concept of “higher order averaging operators along highly fractal stochastic curves”. This approach may provide a general principle for the study of regularization by noise effects in connection with important classes of partial differential equations.
Modelling Turbulent Flow of Superfluid $$^{4}$$He Past a Rough Solid Wall in the $$T =$$ 0 Limit
Authors: Doyle Matthew J. , Golov Andrei I. , Walmsley Paul M. , Baggaley Andrew W. 
Published: March 2024

AbstractWe present a numerical study, using the vortex filament model, of vortex tangles in a flow of pure superfluid $$^4$$

4

He in the $$T = 0$$

T
=
0

limit through a channel of width $$D = 1$$

D
=
1

mm for various applied velocities V. The flat channel walls are assumed to be microscopically rough such that vortices terminating at the walls are permanently pinned; vortices are liberated from their pinned ends exclusively through self-reconnection with their images. Sustained tangles were observed, for a period of 80 s, above the critical velocity $$V_c \sim 0.20$$

V
c

∼
0.20

cm s$$^{-1} = 20 \frac{\kappa }{D}$$

-
1

=
20

κ
D

. The coarse-grained velocity profile was akin to a classical parabolic profile of the laminar Poiseuille flow, albeit with a nonzero slip velocity $$\sim$$
∼
0.20 cm s$$^{-1}$$

-
1

at the walls. The friction force was found to be proportional to the applied velocity. The effective kinematic viscosity was $$\nu ' \sim 0.1\kappa$$

ν
′

∼
0.1
κ

, and effective Reynolds numbers within $$\mathrm {Re'} < 200$$

Re
′

<
200

. The fraction of the polarised vortex length varied between zero in the middle of the channel and $$\sim$$
∼
60% within the shear flow regions $$\sim D/4$$

∼
D
/
4

from the walls. Therefore, we studied a state of statically polarised ultraquantum (Vinen) turbulence fuelled at short length scales by vortex reconnections, including those with vortex images due to the relative motion between the vortex tangle and the pinning rough surface.
An ensemble of artificial neural network models to forecast hourly energy demand
Authors: Manno Andrea , Intini Manuel , Jabali Ola , Malucelli Federico , Rando Dario 
Published: March 2024

AbstractWe propose an ensemble artificial neural network (EANN) methodology for predicting the day ahead energy demand of a district heating operator (DHO). Specifically, at the end of one day, we forecast the energy demand for each of the 24 h of the next day. Our methodology combines three artificial neural network (ANN) models, each capturing a different aspect of the predicted time series. In particular, the outcomes of the three ANN models are combined into a single forecast. This is done using a sequential ordered optimization procedure that establishes the weights of three models in the final output. We validate our EANN methodology using data obtained from a A2A, which is one of the major DHOs in Italy. The data pertains to a major metropolitan area in Northern Italy. We compared the performance of our EANN with the method currently used by the DHO, which is based on multiple linear regression requiring expert intervention. Furthermore, we compared our EANN with the state-of-the-art seasonal autoregressive integrated moving average and Echo State Network models. The results show that our EANN achieves better performance than the other three methods, both in terms of mean absolute percentage error (MAPE) and maximum absolute percentage error. Moreover, we demonstrate that the EANN produces good quality results for longer forecasting horizons. Finally, we note that the EANN is characterised by simplicity, as it requires little tuning of a handful of parameters. This simplicity facilitates its replicability in other cases.
Instant plastic waste detection on shores using laser-induced fluorescence and associated hyperspectral imaging
Authors: Mahmoud Alaaeldin , El-Sharkawy Yasser H. 
Published: March 2024

AbstractPlastic pollution is a rising environmental issue, with millions of tons of plastic debris collecting in the world's seas and on its shores. Hyperspectral imaging (HSI) has become increasingly widely used as a more precise approach that can identify targets in remote sensing aquatic missions. The interference from other beach materials, and the need for proper identification of litter types can make identifying dumped plastics on sand-surrounded beaches challenging. This study lays the groundwork for a physical laboratory setting for images captured by a hyperspectral (HS) imager. The suggested testing setup included the development of a fluorescence signature for the target theater of operations (low-density polyethylene (LD-PE) and wood surrounded by sand) for detecting polymers in a simulated beach environment using the laser-induced fluorescence (LIF) approach. Initially using broadband-spectrum light, strong sample diffuse reflectance contrast is observed in the imaging at wavelengths between 400 and 460 nm. Next, a dedicated LIF system for plastic litter discovery was developed using an ultraviolet (UV) laser source. Initial findings show that there is a distinct fluorescence signal for plastics at 450 nm and at 750 nm for wood. Our pilot studies support current efforts to determine the optimum spectral signature that these polymers will appear with clarity on shorelines using an inexpensive imagery combined with our UV LIF approach, which may have an impact on applications for the detection of beach pollution. The knowledge gained from this study can be used to construct reliable aerial conventional cameras for plastic waste environmental monitoring and management.
Population Dynamics and Policies in Europe: Analysis of Population Resilience at the Subnational and National Levels
Authors: Deimantas Vytenis Juozas , Şanlıtürk A. Ebru , Azzollini Leo , Köksal Selin 
Published: March 2024

AbstractWhile previous research has focused on the relationship between population dynamics and policies in Europe, there has been scarce attention on dynamics at the NUTS-3 level. By looking at the population measures at subnational regions in Europe we seek to identify average population dynamics since year 2000. We group subnational regions by countries in terms of average population dynamics and assess the connection between population policies in 1996 and average population dynamics in 2000–2017 using data from World Population Policy database, the UN Population Division, the World Bank’s World Development Indicators and Eurostat. We find that urban areas and Western and Northern Europe exhibit population growth whilst rural areas and Central, Eastern, and Southern Europe have more depopulating regions. Our analyses also suggest a negative association between fertility policies and population growth.