bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adult childhood cancer survivors’ perceptions of factors that influence their ability to be physically active
Authors: Jess Laura , Bäck Maria , Jarfelt Marianne 
Published: June 2023

Abstract
Purpose
Studies indicate that adult childhood cancer survivors do not achieve recommended physical activity levels. A deeper understanding of factors that influence their ability to be physically active is essential to identify individuals in need of support. The aim was to explore factors that influence adult childhood cancer survivor’s ability to be physically active.

Method
Semi-structured interviews were conducted from June to October 2020 with 20 adult childhood cancer survivors with a median age of 31 (min–max 20–47) years. Interviews were transcribed verbatim and analyzed with qualitative content analysis.

Results
Four main categories: “The impact of environmental factors,” “Personal factors of importance,” “Consequences of the treatment or disease,” and “The impact of support from healthcare” and 10 sub-categories, were identified. Participants described how family habits and encouragement from others influenced their present ability to be physically active. Experienced benefits of physical activity were described as a facilitator for current physical activity while suffering from late complications was identified as a barrier. Participants highlighted the importance of specific and individualized physical activity recommendations.

Conclusion
This study includes adult childhood cancer survivors several years after completion of treatment, hence highlighting the importance for support both during treatment and follow-up to sustain their physical activity. Healthcare providers need to identify individuals suffering from late complications, even several years after treatment; provide individualized physical activity recommendations; and educate families and schools about the importance of physical activity in childhood cancer survivorship.

Trial registration
This research project was registered in the Swedish National Database of Research and Development, identifier 273320, December 6, 2019 (https://www.researchweb.org/is/vgr/project/273320)
RamanNet: a generalized neural network architecture for Raman spectrum analysis
Authors: Ibtehaz Nabil , Chowdhury Muhammad E. H. , Khandakar Amith , Kiranyaz Serkan , Rahman M. Sohel , Zughaier Susu M. 
Published: June 2023

AbstractRaman spectroscopy provides a vibrational profile of the molecules and thus can be used to uniquely identify different kinds of materials. This sort of molecule fingerprinting has thus led to the widespread application of Raman spectrum in various fields like medical diagnosis, forensics, mineralogy, bacteriology, virology, etc. Despite the recent rise in Raman spectra data volume, there has not been any significant effort in developing generalized machine learning methods targeted toward Raman spectra analysis. We examine, experiment, and evaluate existing methods and conjecture that neither current sequential models nor traditional machine learning models are satisfactorily sufficient to analyze Raman spectra. Both have their perks and pitfalls; therefore, we attempt to mix the best of both worlds and propose a novel network architecture RamanNet. RamanNet is immune to the invariance property in convolutional neural networks (CNNs) and at the same time better than traditional machine learning models for the inclusion of sparse connectivity. This has been achieved by incorporating shifted multi-layer perceptrons (MLP) at the earlier levels of the network to extract significant features across the entire spectrum, which are further refined by the inclusion of triplet loss in the hidden layers. Our experiments on 4 public datasets demonstrate superior performance over the much more complex state-of-the-art methods, and thus, RamanNet has the potential to become the de facto standard in Raman spectra data analysis.
Effects of data time lag in a decision-making system using machine learning for pork price prediction
Authors: Suaza-Medina Mario E. , Zarazaga-Soria F. Javier , Pinilla-Lopez Jorge , Lopez-Pellicer Francisco J. , Lacasta Javier 
Published: June 2023

AbstractSpain is the third-largest producer of pork meat in the world, and many farms in several regions depend on the evolution of this market. However, the current pricing system is unfair, as some actors have better market information than others. In this context, historical pricing is an easy-to-find and affordable data source that can help all agents to be better informed. However, the time lag in data acquisition can affect their pricing decisions. In this paper, we study the effect that data acquisition delay has on a price prediction system using multiple prediction algorithms. We describe the integration of the best proposal into a decision support system prototype and test it in a real-case scenario. Specifically, we use public data from the most important regional pork meat markets in Spain published by the Ministry of Agriculture with a two-week delay and subscription-based data of the same markets obtained on the same day. The results show that the error difference between the best public and data subscription models is 0.6 Euro cents in favour of the data without delay. The market dimension makes these differences significant in the supply chain, giving pricing agents a better tool to negotiate market prices.
Inclined Block Impacts on Granular Strata: Coupled DEM-FDM Numerical Investigation and Rheological Modelling
Authors: di Prisco C. , Redaelli I. , Zerbi M. 
Published: June 2023

AbstractIn mountain regions, rockfall is a very widespread natural hazard, difficult to be numerically simulated, from the initial detachment of the block to its impact on natural/artificial strata. When a rock block impacts on a granular stratum, the interaction is dominated by inertial effects and is severely affected by block mass, shape, velocity magnitude/direction, and soil geomechanical properties. The kinematic description of the response of the block during the impact requires complex and time-consuming numerical modeling approaches. Moreover, these numerical approaches cannot be easily coupled with classical mass-lumped rockfall analysis tools employed to simulate blocks trajectory. To overcome this problem, a dynamic upscaled visco-plastic rheological model (BIMPAM), suitable for simulating inclined impacts on generally inclined deformable strata, has been conceived in the past by one of the authors. Up to now, due to the absence of suitable numerical and experimental data, BIMPAM has been only validated on experimental large-scale vertical impacts on horizontal strata. In this paper, the impact problem is analyzed, by performing numerical analyses by means of a coupled Discrete Element and Finite Difference numerical model (DEM-FDM), calibrated on available experimental data, to provide (i) a novel numerical dataset highlighting the crucial role played by the impacting velocity inclination on the dynamic interaction between soil stratum and penetrating rigid object and (ii) a detailed micromechanical description identifying the processes responsible for the complex macroscopic behavior. The obtained numerical results have allowed to both validate BIMPAM model, even in case of inclined velocities, and provide a micromechanical interpretation of its constitutive assumptions.
Rock recognition and identification for selective mechanical mining: a self-adaptive artificial neural network approach
Authors: Xu Rachel , Sellers Ewan J. , Fathi-Salmi Ebrahim 
Published: June 2023

AbstractIn situ characterisation of rock is crucial for mine planning and design. Recent developments in machine learning (ML) have enabled the whole learning, reasoning, and decision-making process to be more efficient and accurate. Despite these developments, the application of ML in rock-cutting is at an early stage due to the lack of mining applications of mechanised excavation leading to limited availability of data sets and the lack of the expert knowledge required when fine-tuning models. This study presents a novel approach for rock identification during mechanical mining by applying a self-adaptive artificial neural network (ANN) model to classify the rock types for selective cutting, in which datasets from two novel cutting operations (actuated disc cutting (ADC) and oscillating disc cutting (ODC)) were employed to test and train a model. The model was also configured with the Bayesian optimization algorithm to determine optimal hyperparameters in an automated manner. By comparing the performance of each evaluation, the model was trained to identify the best set of hypermeters at which uncertainty is minimal. Further testing indicated the model is very accurate in classifying rock types for ADC as the accuracy, recall, and precision all equal unity. Some misclassifications occurred for ODC with the accuracy, recall, and precision ranging from 0.68 to 0.99. The promising results proved the model is a robust and scalable tool for classifying the rock types for selective cutting operations enabling the interpretation to be performed more precisely, selectively, and efficiently. Since mechanical cutting requires significant energy, any improvement in matching machine characteristics to the rock mass will increase productivity, and energy efficiency and reduce cost.
Activity triangles: a new approach to measure activity spaces
Authors: Sila-Nowicka Katarzyna , Fotheringham A. Stewart , Demšar Urška 
Published: June 2023

AbstractThere is an on-going challenge to describe, analyse and visualise the actual and potential extent of human spatial behaviour. The concept of an activity space has been used to examine how people interact with their environment and how the actual or potential spatial extent of individual spatial behaviour can be defined. In this paper, we introduce a new method for measuring activity spaces. We first focus on the definitions and the applications of activity space measures, identifying their respective limitations. We then present our new method, which is based on the theoretical concept of significant locations, that is, places where people spent most of their time. We identify locations of significant places from GPS trajectories and define the activity space of an individual as a set of the first three significant places forming a so-called “activity triangle”. Our new method links the distances travelled for different activities to whether or not people group their activities, which is not possible using existing methods of measuring activity spaces. We test our method on data from a GPS-based travel survey across three towns is Scotland and look at the variations in size and shape of the designed activity triangle among people of different age and gender. We also compare our activity triangle with five other activity spaces and conclude by providing possible routes for improvement of activity space measures when using real human movement data (GPS data).
Heterogeneous effects of cytotoxic chemotherapies for platinum-resistant ovarian cancer
Authors: Nara Katsuhiko , Taguchi Ayumi , Yamamoto Takehito , Hara Konan , Tojima Yuri , Honjoh Harunori , Nishijima Akira , Eguchi Satoko , Miyamoto Yuichiro , Sone Kenbun , Mori Mayuyo , Takada Tappei , Osuga Yutaka 
Published: June 2023

Abstract
Background
Single-agent chemotherapy with or without bevacizumab (Bev) is a standard therapy for platinum-resistant ovarian cancer (PR-OC). However, there is a lack of literature on chemotherapy agent selection in heterogenous PR-OC. Therefore, we aimed to clarify the heterogeneous treatment effects of each chemotherapy agent.

Methods
Patients who underwent single-drug chemotherapy agents or Bev combination therapy for PR-OC between January 2009 and June 2022 were included in this study. We assessed the impact of each chemotherapy agent on the time to treatment failure (TTF) according to histological type, platinum-free interval (PFI), and Bev usage.

Results
A total of 158 patients received 343 different chemotherapy regimens. In patients with clear cell carcinoma/mucinous carcinoma (CC/MC), gemcitabine (GEM) had the strongest effect with a median TTF of 5.3 months, whilst nedaplatin (NDP) had the lowest effect with a median TTF of 1.4 months. In contrast, in the non-CC/MC group, irinotecan (CPT-11) and NDP had a better TTF than GEM and pegylated liposomal doxorubicin (PLD). There were notable differences in the treatment efficacy of NDP according to PFI. Specifically, NDP prolonged the TTF in patients with a PFI ≥ 3 months. Compared with GEM alone, GEM + Bev tended to prolong the TTF more effectively; however, an additive effect was not observed with PLD + Bev.

Conclusions
This study demonstrated that the effect of chemotherapy agents differed according to the tumor and background characteristics of the patient. Our findings will improve selection of effective therapies for patients with PR-OC by considering their background characteristics.
Modularity explains large-scale reef booms in Earth’s history
Authors: Raja Nussaïbah B. , Pandolfi John M. , Kiessling Wolfgang 
Published: June 2023

AbstractDrivers of reef decline are well known both today and in the geological past. Considerably less is known about the preconditions for a pantropical expansion of coral reefs. The geological record of reef building is characterised by considerably long intervals with very limited reef expansion and geologically brief (< 20 million years) episodes of prolific, pantropical reef growth. Here, we propose a new "co-occurrence hypothesis" (COH), which posits that reefs thrive when fast-growing hypercalcifiers co-occur with encrusting organisms such as calcifying microbes or coralline algae to construct wave-resistant structures. While there is little evidence of the effect of abiotic drivers on reef proliferation, we find that positive co-occurrence patterns are significantly more common in reefal as compared to non-reefal communities, suggesting that biological interactions are more relevant in reefs than in non-reefs. Supporting COH, we also show that reefs after the end-Permian mass extinction became more modular in nature with limited membership in reef assemblages during reef booms than in typical periods of reef growth (background intervals). Modularity in reefs may have led to the stabilisation of reef ecosystems, giving them the ability to recover from small perturbations, promoting reefal carbonate accretion and prolific reef growth.
Lohnen sich Maßnahmen gegen Arbeitsstress?
Authors: Angerer Peter , Gündel Harald 
Published: June 2023

ZusammenfassungArbeitsstress erhöht substanziell das Risiko für schwere Erkrankungen wie Depressionen oder Herzinfarkte. Die selektive Literaturübersicht zeigt, dass Interventionen zur Verbesserung der psychosozialen Arbeitsbedingungen sich effektiv auf die Gesundheit der Beschäftigten auswirken und gleichzeitig den wirtschaftlichen Erfolg eines Betriebs erhöhen. Partizipation an den Entscheidungs- und Veränderungsprozessen im Betrieb und Wahrnehmung eigener Handlungskontrolle scheinen zentrale Wirkfaktoren zu sein. Ein gutes psychosocial safety climate (PSC), die Wahrnehmung der Beschäftigten, dass der Betrieb sich um ihre Gesundheit bemüht, sagt bessere Gesundheit und wirtschaftlichen Erfolg voraus.
Older consumers and technology: A critical systematic literature review
Authors: Franco Paolo 
Published: June 2023

AbstractOlder consumers’ adoption and consumption of technologies continues to be an important research area. However, marketing scholarship on this topic risks unintentionally smuggling age stereotypes into its constructed theories. Such assumptions include older consumers’ adoption processes being complicated by health and social isolation issues and their low tech-skills. Although stereotypes hold a ‘kernel-of-truth’ and underpin meaningful research, they can transform from helpful heuristics to impediments to crafting reflexive scholarship. Therefore, this article reviews marketing literature on older consumers and technology. It develops a 2 × 3 typology to analyse 86 articles based on their portrayals of older consumers’ capabilities (incapable/capable) and technology orientations (resisting/discerning/seeking). The typology’s six emergent categories aim to turn age stereotypes into ‘productive tensions’ for researchers by encouraging critical reflexivity in ways that broaden future research possibilities. These possibilities include better accounting for older consumers who are skilled technology-seekers, and equally, non-adopters with non-technophobic reasons to resist adoption.
VmPacC-mediated pH regulation of Valsa mali confers to host acidification identified by comparative proteomics analysis
Authors: Xu Liangsheng , Liu Hailong , Zhu Shan , Meng Yangguang , Wang Yinghao , Li Jianyu , Zhang Feiran , Huang Lili 
Published: June 2023

AbstractApple valsa canker caused by the Ascomycete fungus Valsa mali is one of the most serious diseases of apple, resulting in huge economic losses in the apple-growing area of China. Previous study found that the pathogen could acidify the infected tissues to make lower ambient pH (from 6.0 to 3.5) for their successfully colonization. The pH signaling transcription factor VmPacC is required for acidification of its environment and for full virulence in V. mali. It is known that the functional cooperation of proteins secreted by V. mali plays pivotal role in its successful colonization of host plants. In this study, we used tandem mass tag (TMT) labeling coupled with LC-MS/MS-based quantitative proteomics to analyze the VmPacC-mediated pH regulation in V. mali, focusing on differentially expressed proteins (DEPs). We identified 222 DEPs specific to VmPacC deletion, and 921 DEPs specific to different pH conditions (pH 6.0 and 3.4). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that these DEPs were mainly involved in pathways associated with carbon metabolism, biosynthesis of antibiotics, citrate cycle (TCA cycle), glycolysis/gluconeogenesis, glutathione metabolism, ribosomes, and pentose phosphate pathways. Additionally, we identified 119 DEPs that were shared among the VmPacC deletion mutant and different pH conditions, which were mainly related to energy metabolism pathways, providing the energy required for the hyphal growth and responses to environmental stresses. A protein-protein interaction (PPI) network analysis indicated that most of the shared proteins were mapped to an interaction network with a medium confidence score of 0.4. Notably, one uncharacterized protein (KUI69106.1), and two known proteins (heat shock protein 60 (KUI73579.1), aspartate aminotransferase (KUI73864.1)) located in the core of the network were highly connected (with ≥ 38 directed edges) with the other shared DEPs. Our results suggest that VmPacC participates in the pathogen’s regulation to ambient pH through the regulation of energy metabolism pathways such as the glycolysis/gluconeogenesis pathway and TCA cycle. Finally, we proposed a sophisticated molecular regulatory network to explain pH decrease in V. mali. Our study, by providing insights into V. mali regulating pH, helps to elucidate the mechanisms of host acidification during pathogen infection.
Successful COVID-19 Contact Tracing of Crew from Two Cargo Ships at the Morowali Seaport, Indonesia
Authors: Pane Masdalina , Rahman M. Aulia , Maemun Siti , Purnama Tri Bayu 
Published: June 2023

Abstract

Objectives:
This study aims to report a successful systematic quarantine of coronavirus disease (COVID-19) to detect Omicron, a new variant of concern, among 2 cargo ships in the Morowali seaport, Indonesia.

Methods:
An international standard entry point protocol had been followed in this study for all crew. Rapid diagnostic tests and whole-genome sequencing (WGS) tests have been conducted to identify Omicron, the variant of concern. Individual characteristics, laboratory result, and vaccine status were collected in this study.

Results:
On December 9 and 18, 2021, there was an increase of 21 and 22 new cases, respectively, from 2 ships in the seaport. Both ships came from abroad, 43 new cases with a positivity rate increase from 0 to 13.4% and 13.7% within 2 weeks. A polymerase chain reaction (PCR) examination was carried out on all crews and obtained results 21 of the 22 positive COVID-19 crew (95.5%). The monitoring results showed that there was no fever in the entire crew, no symptoms of cough, runny nose, shortness of breath, and other symptoms pointing to COVID-19.

Conclusion:
Systematic quarantine has successfully contained the large clusters of COVID-19 in the crews of 2 ships and prevented further outbreaks in the local community.
Resilience and health in American Indians and Alaska Natives: A scoping review of the literature
Authors: John-Henderson Neha A. , White Evan J. , Crowder Tony L. 
Published: June 2023

AbstractAmerican Indians and Alaska Natives suffer from disproportionately high rates of chronic mental and physical health conditions. These health inequities are linked to colonization and its downstream consequences. Most of the American Indian and Alaska Native health inequities research uses a deficit framework, failing to acknowledge the resilience of American Indian and Alaska Native people despite challenging historical and current contexts. This scoping review is based on a conceptual model which acknowledges the context of colonization and its consequences (psychological and health risk factors). However, rather than focusing on health risk, we focus on protective factors across three identified domains (social, psychological, and cultural/spiritual), and summarize documented relationships between these resilience factors and health outcomes. Based on the scoping review of the literature, we note gaps in extant knowledge and recommend future directions. The findings summarized here can be used to inform and shape future interventions which aim to optimize health and well-being in American Indian and Alaska Native peoples.