bluuebunny/crossref_metadata_2025_split huggingface dataset:
Patient acceptable symptom state and treatment failure threshold values for work productivity and activity Impairment and EQ-5D-5L in osteoarthritis
Authors: Kiadaliri Ali , Cronström Anna , Dahlberg Leif E. , Lohmander L. Stefan 
Published: February 2024

Abstract
Objective
To estimate patient acceptable symptom state (PASS) and treatment failure (TF) threshold values for Work Productivity and Activity Impairment (WPAI) measure and EQ-5D-5L among people with hip or knee osteoarthritis (OA) 3 and 12 months following participation in a digital self-management intervention (Joint Academy®).

Methods
Among the participants, we computed work and activity impairments scores (both 0–100, with a higher value reflecting higher impairment) and the Swedish hypothetical- (range: − 0.314 to 1) and experience-based (range: 0.243–0.976) EQ-5D-5L index scores (a higher score indicates better health status) at 3- (n = 14,607) and 12-month (n = 2707) follow-ups. Threshold values for PASS and TF were calculated using anchor-based adjusted predictive modeling. We also explored the baseline dependency of threshold values according to pain severity at baseline.

Results
Around 42.0% and 48.3% of the participants rated their current state as acceptable, while 4.2% and 2.8% considered the treatment had failed at 3 and 12 months, respectively. The 3-month PASS/TF thresholds were 16/29 (work impairment), 26/50 (activity impairment), 0.92/0.77 (hypothetical EQ-5D-5L), and 0.87/0.77 (the experience-based EQ-5D-5L). The thresholds at 12 months were generally comparable to those estimated at 3 months. There were baseline dependencies in PASS/TF thresholds with participants with more severe baseline pain considering poorer (more severe) level of WPAI/EQ-5D-5L as satisfactory.

Conclusion
PASS and TF threshold values for WPAI and EQ-5D-5L might be useful for meaningful interpretation of these measures among people with OA. The observed baseline dependency of estimated thresholds limits their generalizability and values should be applied with great caution in other settings/populations.
Towards an Epistemology of ‘Speciesist Ignorance’
Authors: van den Brandeler Emnée 
Published: February 2024

AbstractThe literature on the epistemology of ignorance already discusses how certain forms of discrimination, such as racism and sexism, are perpetuated by the ignorance of individuals and groups. However, little attention has been given to how speciesism—a form of discrimination on the basis of species membership—is sustained through ignorance. Of the few animal ethicists who explicitly discuss ignorance, none have related this concept to speciesism as a form of discrimination. However, it is crucial to explore this connection, I argue, as ignorance is both an integral part of the injustice done to animals as well as an obstacle to improving their treatment. In order to adequately criticize sustained structural speciesism and injustices towards animals, I develop an epistemological account of ‘speciesist ignorance’. I begin by defining and distinguishing between individual and group-based accounts of speciesist ignorance. I argue that humans, taken as a group, enjoy a position of privilege, which allows them to comfortably remain ignorant of their participation in collective wrongdoings towards animals. Additionally, I point out that speciesist ignorance is structurally encouraged and thereby maintains the dominant view that the human-animal-relationship, as it stands, is just. In sum, this article lays the groundwork for a social epistemology of speciesist ignorance. In particular, it informs further debate about individual and institutional epistemic duties to inquire into speciesism and to inform the public, about the moral culpability of ignorant actions, and about effective animal advocacy and policy which actively rejects speciesist ignorance.
Performance and programmability of GrPPI for parallel stream processing on multi-cores
Authors: Garcia Adriano Marques , Griebler Dalvan , Schepke Claudio , García José Daniel , Muñoz Javier Fernández , Fernandes Luiz Gustavo 
Published: February 2024

AbstractGrPPI library aims to simplify the burdening task of parallel programming. It provides a unified, abstract, and generic layer while promising minimal overhead on performance. Although it supports stream parallelism, GrPPI lacks an evaluation regarding representative performance metrics for this domain, such as throughput and latency. This work evaluates GrPPI focused on parallel stream processing. We compare the throughput and latency performance, memory usage, and programmability of GrPPI against handwritten parallel code. For this, we use the benchmarking framework SPBench to build custom GrPPI benchmarks and benchmarks with handwritten parallel code using the same backends supported by GrPPI. The basis of the benchmarks is real applications, such as Lane Detection, Bzip2, Face Recognizer, and Ferret. Experiments show that while performance is often competitive with handwritten parallel code, the infeasibility of fine-tuning GrPPI is a crucial drawback for emerging applications. Despite this, programmability experiments estimate that GrPPI can potentially reduce the development time of parallel applications by about three times.
Training Object Detectors from Scratch: An Empirical Study in the Era of Vision Transformer
Authors: Hong Weixiang , Ren Wang , Lao Jiangwei , Xie Lele , Zhong Liheng , Wang Jian , Chen Jingdong , Liu Honghai , Chu Wei 
Published: February 2024

AbstractModeling in computer vision has long been dominated by convolutional neural networks (CNNs). Recently, in light of the excellent performance of self-attention mechanism in the language field, transformers tailored for visual data have drawn significant attention and triumphed over CNNs in various vision tasks. These vision transformers heavily rely on large-scale pre-training to achieve competitive accuracy, which not only hinders the freedom of architectural design in downstream tasks like object detection, but also causes learning bias and domain mismatch in the fine-tuning stages. To this end, we aim to get rid of the “pre-train and fine-tune” paradigm of vision transformer and train transformer based object detector from scratch. Some earlier works in the CNNs era have successfully trained CNNs based detectors without pre-training, unfortunately, their findings do not generalize well when the backbone is switched from CNNs to a vision transformer. Instead of proposing a specific vision transformer based detector, in this work, our goal is to reveal the insights of training vision transformer based detectors from scratch. In particular, we expect those insights to help other researchers and practitioners, and inspire more interesting research in other fields, such as remote sensing, visual-linguistic pre-training, etc. One of the key findings is that both architectural changes and more epochs play critical roles in training vision transformer based detectors from scratch. Experiments on the MS COCO dataset demonstrate that vision transformer based detectors trained from scratch can also achieve similar performance to their counterparts with ImageNet pre-training.
Olive mill wastes: from wastes to resources
Authors: Enaime Ghizlane , Dababat Salahaldeen , Wichern Marc , Lübken Manfred 
Published: February 2024

AbstractOlive oil extraction has recently experienced a continuous increase due to its related beneficial properties. Consequently, large amounts of olive mill wastes (OMWs) derived from the trituration process are annually produced, causing serious environmental problems. The limited financial capabilities of olive mills make them usually unable to bear the high costs required for the disposal of their wastes. Alternatively, the valorization of OMWs within the framework of the so-called waste-to-resource concept and their recycling can represent a successful strategy for the implementation of circular economy model in the olive industry, which could have significant socioeconomic impacts on low-income Mediterranean countries. There is, however, no unique solution for OMWs valorization, due to the wide variety of the wastes’ composition and their seasonal production. In this review, the potential of OMWs for being reused and the recent technological advances in the field of OMWs valorization are assessed. Special focus is given to the analysis of the advantages and limitations of each technology and to reporting the most significant issues that still limiting its industrial scale-up. The information collected in this review shows that OMW could be effectively exploited in several sectors, including energy production and agriculture. OMWs potential seems, however, undervalued, and the implementation of sustainable valorization strategies in large-scale remains challenging. More efforts and policy actions, through collective actions, encouraging subsidies, and establishing public–private collaborations, are still needed to reconcile research progress with industrial practices and encourage the large-scale implementation of the waste-to-resource concept in the olive sector.
A graph-based approach for modeling the soil–water retention curve of granular soils across the entire suction range
Authors: Yan Wei , Angerer Ludwig , Birle Emanuel , Cudmani Roberto 
Published: February 2024

AbstractThis study investigates experimentally the water retention behavior of granular soils from saturation to oven-dry state. The soil–water retention curve (SWRC) tests were conducted on a well-graded sand with clay using tensiometer and chilled-mirror hygrometer techniques. The soil samples were statically compacted at various water contents to different initial densities. The results showed that individual linear segments in the log–log graph could characterize the desorption process of capillary and adsorption water. A novel water retention model in a simple mathematical form was developed by conceptualizing the total water content as the sum of the suction-dependent capillary and adsorption components. The model parameters possess an unambiguous physical meaning. They can be easily calibrated based on the graphical properties of the test data using simple linear regression, which is a significant advantage over conventional SWRC models. The model was validated using the water retention data of the tested soil in this study and the available data of granular soils in the literature. The reproduced curves agree well with the experimental results. This study also analyzed the influence of compaction water content, initial density, and clay content on the capillary and adsorption components of the water retention curve. Additionally, the proposed framework provides a quick approximation method for the adsorption capacity, which plays an essential role in assessing the effective stress and the simulation of liquid film flow in unsaturated granular soils.
Predicting Risk of Heroin Overdose, Remission, Use, and Mortality Using Ensemble Learning Methods in a Cohort of People with Heroin Dependence
Authors: Marel Christina , Afzali Mohammad H. , Sunderland Matthew , Teesson Maree , Mills Katherine L. 
Published: February 2024

AbstractDespite decades of research demonstrating the effectiveness of treatments for heroin dependence, rates of heroin use, dependence, and death have dramatically increased over the past decade. While evidence has highlighted a range of risk and protective factors for relapse, remission, and other outcomes, this presents clinicians with the challenge as to how to synthesise and integrate the evolving evidence-base to guide clinical decision-making and facilitate the provision of personalised healthcare. Using data from the 11-year follow-up of the Australian Treatment Outcome Study (ATOS), we aimed to develop a clinical risk prediction model to assist clinicians calculate the risk of a range of heroin-related outcomes at varying follow-up intervals for their clients based on known risk factors. Between 2001 and 2002, 615 people with heroin dependence were recruited as part of a prospective longitudinal cohort study. An ensemble machine learning approach was applied to predict risk of heroin use, remission, overdose, and mortality at 1-, 5-, and 10 + year post-study entry. Variables most consistently ranked in the top 10 in terms of their level of importance across outcomes included age; age first got high, used heroin, or injected; sexual trauma; years of school completed; prison history; severe mental health disability; past month criminal involvement; and past month benzodiazepine use. This study provides clinically relevant information on key risk factors associated with heroin use, remission, non-fatal overdose, and mortality among people with heroin dependence, to help guide clinical decision-making in the selection and tailoring of interventions to ensure that the ‘right treatment’ is delivered to the ‘right person’ at the ‘right time’.
TGFβ2 mediates oxidative stress–induced epithelial-to-mesenchymal transition of bladder smooth muscle
Authors: Geng Jingwen , Zhang Xiaofan , Zhang Yansong , Meng Xiaojia , Sun Jinqi , Zhou Bo , Ma Jun 
Published: February 2024

AbstractBladder outlet obstruction (BOO) is the primary clinical manifestation of benign prostatic hyperplasia, the most common urinary system disease in elderly men, and leads to associated lower urinary tract symptoms. Although BOO is reportedly associated with increased systemic oxidative stress (OS), the underlying mechanism remains unclear. The elucidation of this mechanism is the primary aim of this study. A Sprague–Dawley rat model of BOO was constructed and used for urodynamic monitoring. The bladder tissue of rats was collected and subjected to real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR), histological examination, and immunohistochemical staining. Through bioinformatics prediction, we found that transforming growth factor β2 (TGFβ2) expression was upregulated in rats with BOO compared with normal bladder tissue. In vitro analyses using primary bladder smooth muscle cells (BSMCs) revealed that hydrogen peroxide (H2O2) induced TGFβ2 expression. Moreover, H2O2 induced epithelial-to-mesenchymal transition (EMT) by reducing E-cadherin, an endothelial marker and CK-18, a cytokeratin maker, and increasing mesenchymal markers, including N-cadherin, vimentin, and α-smooth muscle actin (α-SMA) levels. The downregulation of TGFβ2 expression in BSMCs using siRNA technology alleviated H2O2-induced changes in EMT marker expression. The findings of the study indicate that TGFβ2 plays a crucial role in BOO by participating in OS-induced EMT in BSMCs.
Pancreatic Neuroendocrine Microtumors (WHO 2022) Are Not Always Low-Grade Neoplasms: A Case with a Highly Increased Proliferation Rate
Authors: Chouchane Aziz , Kirchner Philipp , Marinoni Ilaria , Sticová Eva , Jirásek Tomáš , Perren Aurel 
Published: February 2024

AbstractTraditionally considered non-functional low proliferative benign neuroendocrine proliferations measuring less than 5 mm, pancreatic (neuro)endocrine microadenomas are now classified as pancreatic neuroendocrine microtumors in the 2022 WHO classification of endocrine and neuroendocrine tumors. This case report discussed the features of an incidentally identified 4.7-mm glucagon-expressing pancreatic neuroendocrine microtumor with MEN1 mutation only, chromosomally stable and an epigenetic alpha-like phenotype. The tumor was associated with an unexplained increased proliferation rate in Ki-67 of 15%. There was no associated DAXX/ATRX deficiency. The presented case challenges the conventional thought of a low proliferative disease of the so-called “pancreatic neuroendocrine microadenomas” and provides additional support to the 2022 WHO classification that also requires grading of these neoplasms. Despite exhibiting molecular features of less aggressive behavior, the case also underscores the biological complexity of pancreatic neuroendocrine microtumors. By recognizing the heterogenous spectrum of neuroendocrine neoplasms, the current case also contributes to ongoing discussions on how to optimize the clinical management of such tumors.
Ultra-thin CdTe film properties enhancement via eco-friendly MgCl2-assisted thermal treatment
Authors: Islam Mohammad Aminul , Nur-E-Alam Mohammad , Hatta S. F. W. Muhamad , Mohafez Hamidreza , Misran Halina , Wahab Yasmin Abdul , Chowdhury Zaira Zaman , Soin Norhayati Binti 
Published: February 2024

AbstractThe thermal treatment of the CdTe thin film in the presence of CdCl2 is a crucial step in the creation of high-efficiency CdTe-based solar cells. The process influences the grain growth, grain boundary passivation, and doping, including CdTe recrystallization, and promotes to building of the photovoltaic junction. However, toxic Cd2+ ions released by the CdCl2, which is highly soluble in water is a major environmental concern of this process. Also, the price of CdCl2 (about 30 cents/gram) that drives up manufacturing costs is another limitation of the current processs. Finding a non-toxic Cl molecule is therefore currently in high demand and key factor for the thermal treatment of CdTe. In this study, MgCl2 was thoroughly explored as an alternative, non-toxic, and somewhat less expensive chlorine-containing chemical for CdTe thermal treatment. CdTe thin films, approximately 1.0 µm thick, were deposited on a glass substrate at 350 ºC using RF magnetron sputtering, and after deposition, different concentrations of MgCl2 (0.2 M, 0.3 M, 0.4 M, and 0.5 M) mixed with 10% methanol were applied to the films for around 10 s, forming a thin MgCl2 coating, followed by the optimized heat treatment at 400 ºC in a nitrogen–oxygen environment. We found that the thermal treatment of CdTe films using MgCl2 showed improved crystallinity, surface morphology, impurity profiles, and carrier density similar to the conventional CdCl2 process. The sample treated with 0.4 M MgCl2 exhibited the best output as obtained the band gap of nearly 1.46 eV, a refractive index of 2.84, a carrier concentration of 9.81E+15 cm−3, and mobility 35.08 cm2/V-S with a moderate resistivity. Our findings show that MgCl2 could be utilized instead of traditional CdCl2 in the current fabrication procedure, which substantially lowers the environmental hazard with a cost-effective production process of CdTe-assembled solar cells.
Effects Influence of Social Media Constructs on Shopping: An Empirical Study on the Prediction of Retail Clothing Sales
Authors: Corallo Angelo , Errico Fabrizio , Fortunato Laura , Spennato Alessandra , De Blasi Cristina 
Published: February 2024

Abstract
In a market characterized by frequent new product placement and their rapid exit, accurate forecasting of the sales is an important goal to guarantee the profitability and long-term survival of companies. This paper follows this line of research and explores the sales data of an Italian clothing company. The objective of this research is to improve sales forecasts.
The data under study were extracted from the corporate datalake of the clothing company analyzed as well as from the company’s official Facebook page using Facebook’s Graph API. The sales forecasting should try to consider all the possible demand influencing factors and also explanatory variables. In this way, the time series perspective is combined with qualitative indicators on the demand side. The approach taken confirms the influence of sales from exogenous variables: there is a delay of 15 days between social communication and the sale of clothing. Social communication, as well as some regular Italian holiday, negatively affects sales. On the other hand, school holidays and some regular Italian holidays have a positive impact on sales. As a result, the advance knowledge of revenue forecasts allows managers to choose suitable marketing strategies.
Chemical conditioning of aerobically digested sludge using polyelectrolytes with different charge densities
Authors: Asghari Mohammadreza , Danesh Shahnaz , Ahmadpour Ali , Malekshahi Mehrdad , Behnamsani Moein 
Published: February 2024

AbstractThis research was carried out to evaluate the effects of different dosages (1.85–4.44 g kg−1 Ts−1) of three cationic polyelectrolytes with charge densities (CD) of 20%, 40%, and 60% on the dewatering properties of an aerobically digested sludge. The sludge was collected from the sludge processing line in a wastewater treatment plant in the city of Mashhad, Iran (MWWTP). To assess the sludge dewatering properties, parameters such as specific resistance to filtration, sludge cluster geometry, filtration rate, and filtrate turbidity and volume were measured. The experimental results were then compared with the effects of a reference polyelectrolyte that was used in the conditioning of the sludge in that treatment plant. The results indicated that the sludge samples treated with the polyelectrolyte of the highest CD matched better dewatering performance than the samples conditioned with the other two polyelectrolytes. This polyelectrolyte (60%CD) presented its best effects at the dosage of 4.07 g kg−1 Ts−1. With this dosage, its performance was similar to the performance of the reference polyelectrolyte at the dosage of 4.44 g kg−1 Ts−1.
Schrödinger-Maxwell equations driven by mixed local-nonlocal operators
Authors: Cangiotti Nicolò , Caponi Maicol , Maione Alberto , Vitillaro Enzo 
Published: February 2024

AbstractIn this paper we prove existence of solutions to Schrödinger-Maxwell type systems involving mixed local-nonlocal operators. Two different models are considered: classical Schrödinger-Maxwell equations and Schrödinger-Maxwell equations with a coercive potential, and the main novelty is that the nonlocal part of the operator is allowed to be nonpositive definite according to a real parameter. We then provide a range of parameter values to ensure the existence of solitary standing waves, obtained as Mountain Pass critical points for the associated energy functionals.
The effectiveness of intercropping and agri-environmental schemes on ecosystem service of biological pest control: a meta-analysis
Authors: Yousefi Maryam , Marja Riho , Barmettler Elias , Six Johan , Dray Anne , Ghazoul Jaboury 
Published: February 2024

AbstractPlant diversification contributes to the ecological intensification of agroecosystems through pest biocontrol services provision. However, the existing evidence for the effectiveness of plant diversification in enhancing pest biocontrol services is highly uncertain across features of plant diversity and biodiversity characteristics. We undertook a comparative meta-analysis focusing on three essential crops (wheat, maize, and soybean) to investigate how diversification schemes in-field (intercropping) and Agri-environmental scheme (AES) around the field (flower strip, hedgerow and field margin) affect arthropod abundance. A random effects analysis was used to determine the role of 10 key factors underlying the effectiveness of plant diversification including biodiversity level and habitat, main and companion plant species, intercropping arrangement, the growth stage of the main crops, type of AES planting scheme, AES planting width, distance from AES plantings and geographical latitude. The overall results revealed that intercropping reduced herbivore and boosted predators and parasitoids abundance significantly, while AES successfully increased predators but not herbivores. Maize intercropping with legume and non-legume plants and row intercropping allowed for effective pest management. The abundance of predators increased in wheat fields immediately adjacent to planting around the field (AES), but this effect declined beyond 5 m from the flower strips. Our results suggest that the response of arthropod abundance to plant diversification is a compromise between spatial management scale, ecological characteristics of arthropod and plant diversification features. These results offer promising pathways for optimizing plant diversification schemes that include functional farm biodiversity across spatial and temporal scales and designing multi-functional landscapes.